Real-Time Construction Project Progress Tacking - DigiNole

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Florida State University Libraries Electronic Theses, Treatises and Dissertations The Graduate School 2007 Real-Time Construction Project Progress Tracking: A Hybrid Model for Wireless Technologies Selection, Assessment, and Implementation Amine Ghanem Follow this and additional works at the FSU Digital Library. For more information, please contact [email protected]

Transcript of Real-Time Construction Project Progress Tacking - DigiNole

Florida State University Libraries

Electronic Theses, Treatises and Dissertations The Graduate School

2007

Real-Time Construction Project ProgressTracking: A Hybrid Model for WirelessTechnologies Selection, Assessment, andImplementationAmine Ghanem

Follow this and additional works at the FSU Digital Library. For more information, please contact [email protected]

THE FLORIDA STATE UNIVERSITY

COLLEGE OF ENGINEERING

REAL-TIME CONSTRUCTION PROJECT PROGRESS TRACKING: A HYBRID MODEL FOR WIRELESS TECHNOLOGIES SELECTION, ASSESSMENT, AND

IMPLEMENTATION

By

AMINE GHANEM

A Dissertation submitted to the Department of Civil and Environmental Engineering

in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

Degree Awarded: Summer Semester, 2007

ii

The members of the Committee approve the Dissertation of Amine Ghanem defended on June 8, 2007.

________________________

Yassir A. AbdelRazig Professor Directing Dissertation

________________________

Jeffrey R. Brown Outside Committee Member

________________________

John O. Sobanjo

Committee Member

________________________

Wei-Chou V. Ping Committee Member

Approved: ___________________________________________________________

C. J. Chen, Dean, College of Engineering, Florida State University

The Office of Graduate Studies has verified and approved the above named committee members.

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To My parents,

Abdallah and Aicha And my sisters

Lina, Dima, and Nadine Who made all of this possible

For their endless encouragement and support

And also to My fiancé

Nermine Majzoub For her love and patience

iv

ACKNOWLEDGEMENTS

First and foremost, I thank Allah for His continuous bounties and guidance

in my life.

This dissertation concludes a learning journey at Florida State University. I

am grateful to many individuals who contributed to my learning experience at

Florida State University.

I would like to express my sincerest thanks to many key people: At the top

of the list, my advisor, Dr. Yassir AbdelRazig for his valuable guidance,

inspiration, and advice. Sincere appreciation is also extended to my committee

members: Dr. Jeffrey R. Brown, Dr. John O. Sobanjo, and Dr. Wei-Chou V. Ping,

who gave their time and input to my research. I would like also to thank Dr.

Garold Oberlender for his unconditional support and valuable advice and

feedback.

The assistance offered by Sperry & Associates and Haskell Company to

collect valuable data should be gratefully acknowledged here.

This research would not have been possible without the people who took

part of the survey I performed, and to whom I have promised anonymity. I am

also very thankful to my colleagues Dr. Mohamad El-Gafy, Mr. Rassem Awwad,

and Mr. Hassan Ghanem whose help in some of the conceptual thinking was

invaluable.

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TABLE OF CONTENTS List of Tables ....................................................................................Page ix List of Figures .....................................................................................Page xi Abstract ..........................................................................................Page xiii Chapter 1 Introduction ............................................................................Page 1 1.1 Background .......................................................................Page 1 1.2 Problem Statement............................................................Page 4 1.3 Research Objectives .........................................................Page 6 1.4 Research Methodology......................................................Page 7 1.4.1 Problem Identification...................................................Page 7 1.4.2 Model Formulation .......................................................Page 8 1.4.3 Model Implementation..................................................Page 8 1.5 Dissertation Organization ..................................................Page 10 Chapter 2 Prior Research Efforts............................................................Page 12 2.1 Project Tracking ................................................................Page 12 2.1.1 Technology in Material Tracking........................................Page 15 2.1.2 Technology in Equipment and Labor Tracking ..................Page 17 2.2 Computer & Wireless Integrated Construction ..................Page 18 2.3 Bar Code ...........................................................................Page 20 2.3.1 Bar Codes Applications in Construction ............................Page 21 2.4 RFID ..................................................................................Page 22 2.4.1 Tags or Transponder.........................................................Page 22 2.4.2 Antenna .............................................................................Page 23 2.4.3 Reader...............................................................................Page 24 2.4.4 RFID Applications in Construction.....................................Page 25 2.5 Construction Site Information ...........................................Page 26 2.5.1 Construction Site Information Needs.................................Page 27 2.5.2 Construction Site Information Users..................................Page 28 2.6 Survey of Wireless Technologies in Construction .............Page 29 2.6.1 Wireless Technologies in Construction..............................Page 29 2.6.2 Barriers to Wireless Applications in Construction ..............Page 30 Chapter 3 Background .......................................................................Page 32 3.1 Wireless Technologies ......................................................Page 32 3.1.1 Mobile Hardware ...............................................................Page 32 3.1.1.1 Personal Digital Assistants...........................................Page 33 3.1.1.2 Handheld Computers ...................................................Page 33

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3.1.1.3 Pen Tablet/Touch PC...................................................Page 33 3.1.1.4 Rugged Notebooks ......................................................Page 34 3.1.1.5 Wearable Computers/Digital Hardhats.........................Page 34 3.1.1.6 Digital Pen....................................................................Page 34 3.1.2 Networks............................................................................Page 35 3.1.2.1 Wireless Wide Area Networks......................................Page 36 3.1.2.2 Wireless Local Area Networks .....................................Page 36 3.1.2.3 Satellites Networks.......................................................Page 38 3.1.3 Mobile Applications ............................................................Page 39 3.1.3.1 CAD Applications .........................................................Page 39 3.1.3.2 Data Capture Applications...........................................Page 39 3.1.3.3 Project Management Application..................................Page 40 3.2 Technology Assessment Methods.....................................Page 40 3.2.1 Assumptions and Fundamentals of Utility Theory .............Page 41 3.2.2 Types of Utility Functions .................................................Page 43 3.2.3 Hierarchical Structure of MAUT.........................................Page 45 3.2.3.1 Defining Evaluation Objectives ....................................Page 45 3.2.3.2 Defining Alternative Attributes......................................Page 45 3.2.3.3 Attribute Characteristics ...............................................Page 46 3.2.3.4 Assigning Attribute Weights .........................................Page 46 3.2.4 Analytical Hierarchy Process.............................................Page 48 3.2.4.1 Setting Priorities ..........................................................Page 49 3.2.4.2 Pairwise Comparison Scale.........................................Page 49 3.2.4.3 Eigenvector Prioritization Method ................................Page 50 3.3 Computer Construction Simulation....................................Page 53 3.3.1 General Modeling and Simulation Systems.......................Page 53 3.3.1.1 GPSS...........................................................................Page 54 3.3.1.2 HOCUS ........................................................................Page 54 3.3.1.3 ITHINK.........................................................................Page 55 3.3.1.4 SLAMII.........................................................................Page 55 3.3.2 Construction Simulation Using Networks...........................Page 55 3.3.2.1 Cyclone........................................................................Page 55 3.3.2.2 RESQUE.....................................................................Page 56 3.3.2.3 COOPS........................................................................Page 57 3.3.2.4 CIPROS ......................................................................Page 57 3.3.2.5 STROBOSCOPE ........................................................Page 57 Chapter 4 Real time project progress tracking model ........................Page 59 4.1 Framework for real time project progress tracking.............Page 59 4.2 Hardware and Software Selection .....................................Page 61 4.2.1 Hardware Selection......................................................Page 61 4.2.1.1 Computer Alternatives .................................................Page 61 4.2.1.2 Wireless Infrastructure Alternatives.............................Page 64 4.2.1.3 Smart Chips Alternatives .............................................Page 65 4.2.2 Software Selection .......................................................Page 66

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4.3 Implementation Steps........................................................Page 66 4.3.1 Work Progress Measurement ......................................Page 69 4.4 Construction of Data Management System ......................Page 69 4.4.1 Data Dictionary..................................................................Page 70 4.4.2 Project Database...............................................................Page 73 4.4.2.1 Database Queries ........................................................Page 74 Chapter 5 Technology Selection and Assessment..................................Page 77 5.1 Assessment Model ............................................................Page 77 5.1.1 Defining the Problem.........................................................Page 77 5.1.2 Explanation of Model Attributes.........................................Page 79 5.1.3 Defining Attribute Measuring Scales..................................Page 82 5.2 Utility Function Survey.......................................................Page 83 5.2.1 Measuring Weights............................................................Page 84 5.2.2 Consistency Checks..........................................................Page 86 5.3 Procedure for Constructing Single AUF.............................Page 89 5.3.1 Multiple Attribute Utility Function Development .................Page 91 5.4 Sensitivity Analysis ............................................................Page 96 5.4.1 Effect of Changing Cost.....................................................Page 96 5.4.2 Effect of Changing Risk Weight.........................................Page 98 Chapter 6 Steel Construction Process Case Studies..............................Page 100 6.1 Case Study........................................................................Page 100 6.1.1 Case Study 1: Turbocor Project ........................................Page 100 6.1.2 Case Study 2: Jefferson County High School Project........Page 102 6.2 Steel Construction Process Overview ...............................Page 104 6.2.1 Preplanning and Fabrication..............................................Page 104 6.2.2 Shipment and Unloading ...................................................Page 105 6.2.3 Steel Erection ....................................................................Page 106 6.3 Model Existing Steel Construction Processes ...................Page 106 6.4 Productivity Measurement .................................................Page 108 6.4.1 PEB Simulation Model.......................................................Page 109 6.4.2 Process Inefficiency...........................................................Page 112 6.5 Steel Construction Process Updated.................................Page 114 6.5.1 Development of a Data Flow Diagram...............................Page 114 6.5.2 Proposed Process .............................................................Page 116 6.5.3 Simulation Model...............................................................Page 118 6.6 Simulation Outputs ............................................................Page 120 6.7 Proposed Model Benefits ..................................................Page 122 6.7.1 Function A: Site Inspection Savings ..................................Page 129 6.7.2 Function B: Problem Solving Savings................................Page 130 6.7.2.1 Cost Benefit Analysis ...................................................Page 132 6.7.2.2 Sensitivity and Break-Even Analysis ............................Page 133 6.7.3 Function C: Wireless Data Access Savings.......................Page 134

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6.7.3.1 Cost Benefit Analysis ...................................................Page 136 6.7.4 Function D: E-Document Management .............................Page 137 Chapter 7 Conclusions and Recommendations......................................Page 139 7.1 Summary of the Research.................................................Page 139 7.2 Research Contribution.......................................................Page 140 7.3 Limitations .........................................................................Page 142 7.4 Recommendations for Future Work...................................Page 142 APPENDICES .....................................................................................Page 144 A Smart Chips...............................................................................Page 144 B Survey .....................................................................................Page 152 C Case Study Documents.............................................................Page 160 D Simulation Input/Output Files ....................................................Page 176 REFERENCES .....................................................................................Page 190 BIOGRAPHICAL SKETCH ....................................................................Page 198

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LIST OF TABLES Table 2.1: Tracking Methods ..................................................................Page 13 Table 3.1: Pairwise Comparison Scale Presented by Saaty ...................Page 50 Table 3.2: Approximated Random Indices RI .........................................Page 52 Table 4.1: Rugged Mobile Device Comparison.......................................Page 63 Table 4.2: Database Dictionary...............................................................Page 71 Table 5.1: Attribute Measures.................................................................Page 82 Table 5.2: Assessment of UL...................................................................Page 90 Table 5.3: Assessment of UH ..................................................................Page 90 Table 5.4: Single Attribute Utility Functions ............................................Page 93 Table 5.5: Technology Alternatives.........................................................Page 94 Table 5.6: Alternatives Measures............................................................Page 94 Table 5.7: Utility of Alternatives Case Study 1 ........................................Page 95 Table 5.8: Utility of Alternatives Case Study 2 ........................................Page 95 Table 5.9: Utility Variations Based on Costs Changes............................Page 97 Table 5.10: Utility Variations Based on Risk Weight Changes................Page 98 Table 6.1: Productivity Ratings ...............................................................Page 109 Table 6.2: Simulated Productivity Results...............................................Page 121 Table 6.3: LCC Input Data ......................................................................Page 123 Table 6.4: LCC Calculation .....................................................................Page 124 Table 6.5: LCC Summary Case Study 1 .................................................Page 127 Table 6.6: LCC Summary Case Study 2 .................................................Page 128

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Table 6.7: Benefits Calculation of Function A Case Study 1...................Page 129 Table 6.8: Benefits Calculation of Function A Case Study 2...................Page 130 Table 6.9: Benefits Calculation of Function B Case Study 1...................Page 131 Table 6.10: Benefits Calculation of Function B Case Study 2.................Page 132 Table 6.11: Cost Benefit Analysis of Function B Case Study 1...............Page 132 Table 6.12: Cost Benefit Analysis of Function B Case Study 2...............Page 132 Table 6.13: Benefits Calculation of Function C .......................................Page 134 Table 6.14: Rework & Process Elimination Savings Case Study 1.........Page 135 Table 6.15: Rework & Process Elimination Savings Case Study 2.........Page 135 Table 6.16: Summary of Benefits of Function C Case Study 1 ...............Page 135 Table 6.17: Summary of Benefits of Function C Case Study 2 ...............Page 135 Table 6.18: Cost Benefit Analysis of Function C Case Study 1 ..............Page 136 Table 6.19: Cost Benefit Analysis of Function C Case Study 2 ..............Page 136 Table 6.20: Benefits Calculation of Function D .......................................Page 137 Table 6.21: Summary of Benefits Case Study 1 .....................................Page 137 Table 6.22: Summary of Benefits Case Study 2 .....................................Page 138

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LIST OF FIGURES Figure 1.1: Construction Labor Productivity ............................................Page 2 Figure 1.2: Research Methodologies .....................................................Page 9 Figure 2.1: Basic Barcode Structure .......................................................Page 20 Figure 2.2: Antenna Sealed with RFID Tag ............................................Page 23 Figure 2.3: Handheld Stationary Readers...............................................Page 24 Figure 2.4: Digital Hardware Used in the Construction ...........................Page 29

Figure 2.5: Cutting Edge Tools Used in the Construction ......................Page 30

Figure 2.6: Barriers to Wireless Applications in Construction .................Page 31 Figure 3.1: Types of Mobile PC’s............................................................Page 35 Figure 3.2: Types of Utility Curves ..........................................................Page 44 Figure 3.3: Sample Comparison Matrix...................................................Page 49 Figure 3.4: Normalized Matrix.................................................................Page 50 Figure 3.5: Eigenvector Matrix ................................................................Page 51 Figure 3.6: Transition Matrix ...................................................................Page 51 Figure 4.1: Model Framework .................................................................Page 60 Figure 4.2: Data Exchange and Reporting..............................................Page 67 Figure 4.3: General System Configuration..............................................Page 68 Figure 4.4: Database Management System............................................Page 70 Figure 4.5: Project Database Tables and their Relationships .................Page 74 Figure 4.6: User Interface .......................................................................Page 75 Figure 4.7: Project Updates ....................................................................Page 75

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Figure 4.8: Erection Drawings.................................................................Page 76 Figure 5.1: Analytic Hierarchy Process ...................................................Page 78 Figure 5.2: Hierarchy of Influence as Applied in the Study .....................Page 81 Figure 5.3: Job Title Survey Respondents ..............................................Page 84 Figure 5.4: Pairwise Comparisons ..........................................................Page 85 Figure 5.5: Consistency Checks .............................................................Page 89 Figure 5.6: Cost Analysis ........................................................................Page 97 Figure 5.7: Risk Weight Analysis ............................................................Page 98 Figure 6.1: Different Construction Phases ..............................................Page 102 Figure 6.2: Aerial View of JCHS Site ......................................................Page 103 Figure 6.3: MSC Panel Fabrication.........................................................Page 103 Figure 6.4: Tilt-Up Panel Wall Erection ...................................................Page 104 Figure 6.5: PEB Fabrication....................................................................Page 105 Figure 6.6: Unloading Steel Members.....................................................Page 105 Figure 6.7: Erection.................................................................................Page 106 Figure 6.8: Materials and Information Flow.............................................Page 107 Figure 6.9: Shipping Simulation Model ...................................................Page 111 Figure 6.10: Erection Simulation Model ..................................................Page 112 Figure 6.11: To Be Materials and Information Flow ................................Page 115 Figure 6.12: Copying Information to the RFID Tags................................Page 117 Figure 6.13: Proposed Shipping Simulation Model .................................Page 119 Figure 6.14: Proposed Erection Simulation Model..................................Page 120 Figure 6.15: Cost-Benefit Chart for Two Variables..................................Page 133

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ABSTRACT

A construction project is considered as a process that involves many

activities and a large amount of information of various types that are related to

each other. Successful project management requires controlling all aspects of a

construction project: quality and quantity of work, costs, and schedules to

guarantee the success of the project. So the construction project control aims to

effectively obtain real-time information of activities taking place on the site.

Meanwhile, paper-based documents of project management used are becoming

ineffective and can’t get quick responses to the office and project control center.

Integrating promising information technologies such as radio frequency

identification (RFID), mobile computing devices, and wireless technology can be

extremely useful for improving the effectiveness and convenience of information

flow in construction projects. The probable benefits are potentially enormous, but

the barriers associated with technology adoption within the construction industry,

currently outweigh this potential.

This research develops a control system for construction projects. The main

objectives of this research include (1) developing a framework for real time

construction project tracking; (2) applying such a system that integrates RFID

technology with mobile computing and wireless technology to increase the

efficiency of jobsite communication and data collection; (3) designing a database

system for construction activities and updates, providing real-time information

and wireless communication between offices and sites, subcontractors and

suppliers; (4) developing a hybrid model for wireless technologies selection,

assessment and implementation; (5) applying the model on pre-engineered steel

construction projects and performing life cycle cost and cost benefit analysis.

This model will greatly increase productivity and efficiency, will reduce labor

hours and time required for tracking.

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CHAPTER 1

INTRODUCTION

1.1 Background

Construction is one of the largest industries in the United States, and its

second largest employer after government agencies. According to an

employment report from the U.S. Bureau Labor Statistics, construction

employment in the U.S. in the second quarter of 2005 account for roughly 7.2

million, or 5.4 percent of non-farm payroll employment (U.S. Census Bureau

2004). Moreover, the value of construction invested, a measure of the amount

spent on design, engineering, and construction, totaled $ 1 trillion in May 2004,

according to the Census Bureau. This amount is equivalent to roughly eight

percent of the U.S. gross domestic product (GDP). However the construction

industry has suffered from low performance due to low productivity, high accident

rates, late completion, and poor quality (Kashiwagi et al., 2004). In 2003, the U.S.

Bureau of Labor Statistics showed that labor productivity in construction has

been lagging behind other U.S. industries (see Figure 1) for the past 40 years.

A study performed by Nuntasunti (2003) summarized five factors

preventing the construction industry from improving performance: 1)

Fragmentation of the construction industry; 2) project specific nature of

construction; 3) temporary nature of relationships; 4) competitive bidding system;

and 5) stand alone islands of communication.

A construction project essentially involves a large amount of information of

various types. This is due to the fact that different parties perform independent

tasks on a project to produce a single final product. Since the design of a project

must somehow be communicated to many parties on the construction site, it is

important that clear information, coherent and efficient communication exist to

ensure successful work by all participants in the project. The specifications must

2

be translated into information that all parties can use in fulfilling their tasks.

Hence, the need for drawings, contracts, specifications, building codes, and other

forms of information emerges. At the same time, the performance of the project

must also be communicated back to management so that it can be controlled

effectively.

Figure 1.1: Construction Labor Productivity Index versus All Non-farm U.S. Industries

As projects become more complex, the amount and detail of the

information required increases. This increase in turn makes the process of

storing, retrieving, and analyzing the control information more complicated and

subject to mistakes. A large amount of information is created by independent

organizations and individuals involved in the project.

One commonly cited means of overcoming labor shortages and improving

productivity, cost effectiveness, and competitiveness is through the use of

advanced technologies such as information technology (Johnson and Tatum

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1993). Information technology (IT) was developed as a means of meeting

complex information demands and of automating the tasks associated with them.

Advances in IT promised great leaps in productivity in the late 20th century,

however few industries have truly profited from IT’s promises. In the same

manner, automation technologies such as robotics offered similar benefits to the

construction industry with few tangible benefits yet realized (Skibniewsky and

Hendrickson 1990, Farid 1993).

The construction industry lags behind other industries in adopting

innovative new technologies. The need to accelerate the rate of technological

adoption in the construction industry has been well documented in the literature

(Mitropoulos and Tatum, 2000). This adoption comes from continuously seeking,

recognizing, and implementing new technologies that improve construction

processes (Laborde and Sanvido 1994). Each technology has its own technical,

economic, and risk considerations that make the selection process a difficult one.

The selection decision involves many tradeoffs among technology attributes.

Unlike the structured environment and highly repetitive processes in

manufacturing, construction poses many barriers to the implementation of

advanced technologies. Characteristic fragmentation, diversity, and fierce

competition of the construction industry combine to make research and

development (R&D) difficult (Tucker 1988). In a fiercely competitive environment

with thin profit margins, individual firms, especially the smaller ones, simply can’t

afford to conduct R&D or pay added regulatory costs of introducing new

technologies. In 1997, the industry spent only 0.6 percent of total revenues on

R&D, whereas most other industries committed 4 to 6 percent. An unfocused and

uncoordinated effort among the various R&D sectors makes this chronic under-

funding worse. The National Institute for Standards and Technology (NIST), the

Department of Transportation, and the Department of Energy sponsor conduct,

or cost-share with industry and academia research activities. The National

Science Foundation (NSF) funds more than 70 percent of academia’s

construction R&D efforts. The Army Corps of Engineer’s Engineering Research

and Development Center and the Naval Facilities Engineer Command’s

4

Engineering Service Center conduct lion’s share of government R&D. The

construction industry has barely just begun to examine ways of integrating its

management processes with information technology into a unified system. Non-

profit organizations such as the Construction Industry Institute (CII) and the

National Institute of Standards and Technology (NIST) are spearheading these

efforts through their FIATECH (Fully Integrated and Automated Technology) and

CONSIAT (Construction Integrated and Automation Technology) programs,

respectively, and are starting to address the barriers that stand in the way along

with research in Enterprise Resource Planning (ERP) in construction at other

institutions (O’Connor and Dodd 2000).

1.2 Problem Statement

During the construction phase of a project it is essential that efficient and

timely flow of information prevail throughout the process. The construction

industry is dynamic by nature and requires that all parties be kept informed of

activities that can ultimately affect the cost, schedule or performance of the work.

The paper-based documentation of site processes is ineffective anymore as it is

unable to deliver just in time information. At the same time paper documentation

can’t get the quick response from the office to the construction site and vice

versa. As a result, a gap in time and space between the job site and office

causes the lack and confusion of data and information. The effectiveness of

information and data acquisition influences the flow of information between the

office and the construction site. Field supervisory personnel on construction site

spend between 30-50% of their time recording and analyzing field data

(McCullouch 1997) and 2% of the work on construction sites is devoted to

manual tracking and recording of progress data (Cheok et al. 2000). Accuracy of

the collected data depends on judgments and writing skills of the people

collecting data (Liu 1995). In addition, since most data items are not captured

digitally, data transfer from a site to a field office requires additional time. When

the required data is not captured accurately or completely, extra communication

5

is needed between the site office and field personnel (Thorpe and Mead 2001).

These extra efforts are time consuming and waste of money. These inefficiencies

are embedded and distributed among many different activities and project

participants, and hence, the project team is generally not aware of the

implications and aggregate time and money waste associated with them.

Wireless technologies can be used to improve the accuracy and timeliness of the

data collected from sites and to improve communication flow. Previous research

on such technologies mainly discussed the technological feasibility of using a

particular technology to support various construction project tasks (Akinci et al.

2005, Jaselskis et al. 1995). But still there is a need for a comprehensive

framework to assess the effectiveness of using such technologies that

encompasses all different merits together: performance, reliability, risk, and cost.

The following section summarizes several problem areas in the

construction that this thesis will address:

(1) Independent islands of communication on the construction site:

Lacks of effective communication among various parties involved in

construction projects make information exchange inefficient. Moreover,

paper-based handling of change orders and Request for Information

(RFIs) increases difficulties in information exchange in a timely manner.

Even though project participants have been using various project

management tools to improve communication, there are still deficiencies

in updating the schedule and the progress of the construction project in a

real time fashion

(2) Obsolete paper-based and as-built drawings:

Paper prints are currently used to exchange design, shop, erection, and

as built drawings between project participants. Duplication of effort,

inconsistencies, errors, missing information, and extensive time needed to

find relevant information are common in paper-based documents.

(3) Decrease in productivity created by ineffective flow of information:

This problem is created by lack of information about availability of

materials on the construction site. Materials handling and storing is also a

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problem. Time is commonly wasted trying to figure out where materials

are on the construction site, and whether or not there is enough quantity.

(4) Lack of assessing method for decision makers to select a

technology:

Each technology has its own technical, economic and risk consideration

that make the selection process difficult. Considering one aspect in

choosing and ignoring the others may not lead to the optimal decision.

Currently there are no tool that rationalizes and facilitates this complicated

decision making process.

1.3 Research Objectives

The overall objective of this research is to develop a hybrid model, based

on a combination of Radio Frequency Identification tags (RFID), mobile

computing, and wireless technologies in tracking the progress of construction

project. This research develops a project progress control system for

construction projects. Mainly, the control system is a central database that will

provide real-time and updated information for different parties on a construction

project. In addition, a multi-attribute utility model is developed to help decision

makers select the appropriate IT to the required construction application. Two

pre-engineered steel construction buildings are used as case studies application

of the proposed model

The detailed objectives of this research include:

(1) Investigating integration of RFID technology with Mobile computing and

wireless technology as a communication and data collection tool for

construction jobsite.

(2) Designing a central Database for construction activities and updates,

providing real-time information and facilitating wireless communication

between offices and sites, subcontractors and suppliers.

(3) Developing a framework for real-time construction project tracking.

7

(4) Developing a hybrid model for wireless technologies selection,

assessment and implementation.

(5) Applying the model on a pre-engineered steel construction and performing

a life cycle cost and cost benefit analysis, to illustrate the model

framework.

1.4 Research Methodology

This research is divided into three main phases: problem identification

phase, model formulation phase, and system implementation through real case

studies. Each phase includes several steps to achieve the objectives of that

particular phase. Figure 1.2 illustrates the different phases and steps for the

research methodology.

1.4.1 Problem Identification

This phase include reviewing current practices of project progress tracking

and information flow on the construction site to pinpoint the deficiencies in these

practices. The objective of this step is to establish the need for a more efficient,

up-to-date, and reliable practice for project control and monitoring. Another step

is reviewing the use of smart chips and wireless technologies in construction, and

discussing the different application of each technology. Moreover, another step is

to review a survey conducted by ASCE to identify barriers to wireless application.

The objective of the previous two steps is to find ways of to implement

technologies in construction and how to overcome the barriers to its

implementation.

The objectives of the problem identification phase are to define the scope

of the research and to establish the background necessary to accomplish the

research objectives. The focus of the research is to develop a framework for real

time project tracking, and to develop a hybrid assessment model for wireless

technologies. The system is considered hybrid because it uses two quantification

methods in assessment: subjective and objective.

8

1.4.2 Models Formulation

The first step in this phase is to acquire and set up the hardware and

software required for the different phases of the research. Another step is to

establish the procedure of how resources on the construction site will be tracked,

by identifying the appropriate type of measurement method. This step is

achieved by investigating each activity in the main schedule, and assigning the

appropriate resources whether it is equipment, materials or labors resources.

The following step is to develop a central database where all information

captured on the construction site is sent to this database. This step is achieved

by creating different kind of relationships between the proposed tables using

Microsoft access. In this case SQL is used to establish appropriate queries.

The next step is to choose the right hardware and software for the real-

time tracking model by formulating a multi attribute utility model. The main part of

this stage is to construct a hierarchy of influence that includes the main objective,

criteria of evaluation and alternatives to be assessed. Then it uses eigenvector

prioritization method to develop a hybrid model for wireless selection and

assessment. The objective of this phase is to formulate the basic structure of the

hybrid assessment model for wireless technologies selection.

1.4.3 Model Implementation

The final stage of the research is utilizing case studies from construction

projects, in the State of Florida, to illustrate and apply the framework of real-time

project progress tracking. This step is achieved by formulating an information

flow model of steel construction, and then performing simulation of different cycle

of the project to quantify the benefits of the proposed model.

The next step would be to synthesize all the previous steps to finalize and

refine the framework. More examples, if needed, would be used to validate the

reliability of the framework and necessary adjustments will be made. Finally, the

write-up of the completed dissertation will be provided.

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Figure 1.2: Research Methodology

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1.5 Dissertation Organization

This thesis is organized into seven chapters. Chapter 1 gives an overview

of project progress tracking problems in the construction industry and

emphasizes on the importance of data exchange and communication among

project parties. This chapter also sheds some light on the lack of information to

assess usage of wireless technologies in construction. Research problem

statement and objectives are also presented. Chapter 2 describes available

technologies necessary for conducting this research. At the same time a

summary of previous research that has been done in this field is presented. Then

the results of a survey conducted by the ASCE Construction Institute Wireless

Committee to identify barriers to wireless technologies application in construction

are discussed. Chapter 3 lays down the background to conduct this research. It

starts with identifying different wireless technologies: hardware and software.

Then different methods to assess technologies are presented. Finally, the

chapter is completed with a description of computer simulation in construction.

Chapter 4 presents the developed construction project progress-tracking model

based on wireless technologies. This model provides updates in real-time

allowing the user to track the progress of percentage completed on the

construction site and to access project information from a central database.

Chapter 5 describes a quantitative process to select and assess the appropriate

IT to be used in the proposed real-time system using multi-attribute utility theory.

Chapter 6 presents two case studies for pre-engineered steel buildings where the

proposed model is applied. A detailed study of pre-fabricated steel process will

be discussed to show how the model functions. Then a simulation model of the

pre-engineered steel process is presented in order to illustrate the benefits of

applying the model. Conducting a value assessment analysis to quantify the

benefits concludes this chapter. Chapter 7 concludes the thesis with a summary,

conclusions, and recommendations for future study. Research contributions and

limitations are also outlined in this chapter. The appendices contain detailed

information of some of the issues discussed in the thesis. Appendix A contains

11

information about smart chips. Appendix B contains information of the survey

conducted in this research. Appendix C contains information about the data

gathered from both case studies. Appendix D contains information about the

simulation input and output files.

12

CHAPTER 2

PRIOR RESEARCH EFFORTS

This chapter lays necessary foundation for the research and includes

review of prior research efforts. The literature review of prior research efforts

includes reviewing the application of information technologies and the use of

barcode and Radio Frequency Identification (RFID) in the construction industry

and discusses the different application of each technology. In addition to the use

of smart chips, this chapter describes wireless technologies and its application on

the construction site. Then an ASCE survey presented by the CI wireless

committee is presented to identify barriers to wireless application. Finally the

needs for information and for users on the construction site are identified.

2.1 Project Tracking

A simple project can be planned as a list of tasks with their start and finish

dates written on a piece of paper. A complex plan on the other hand, might deal

with thousands of tasks, resources, and a project budget of billions of dollars. As

the project becomes more and more complex, so does the requirement for a

project management system. It is a good practice to monitor a project’s

performance continuously throughout its various phases in order to maintain

certain cost, time, quality, and safety criteria. This will also help ensure that a

project can be completed within budget, on schedule, at the desired quality, and

with an acceptable safety record.

One of the main way of controlling a project’s quality, cost, and schedule

performance is to continuously monitor activities during the construction phase in

order to keep track of work done: materials and equipments used versus installed

13

quantities. These quantities can then be compared against quantities estimated

during the planning phase to gauge the project’s performance.

Construction Industry Institute (CII) uses six different methods to measure

the work progress at the construction jobsite, depending on the type of work to

be done. Table 2.1 summarizes these methods.

Table 2.1: Tracking Methods (adapted from CII 1987a) Method Suitable for Measuring Examples

Units Completed

Activities that involve repeated production of easily measured work packages that consume roughly equal resources

Linear feet of wire or pipe installed, or cubic yards of concrete placed, etc.

Incremental Milestone

Sequential activities with clearly defined milestones

Pipe received/inspected, pipes supported, pipes aligned, pipes welded, pipes tested, pipes completed

Start/Finish Activities that do not have interim milestones or that are hard to quantify in terms of time and cost

Cleaning, testing, aligning, etc.

Supervisor Opinion

Minor activities where detailed analysis is not necessary

Painting, constructing support facilities, etc.

Cost Ratio Long term activities that may span the life of a project and are allocated bulk cost/time

Project management, quality assurance, etc.

Weighted or Equivalent Units

Long term activities that include multiple subtasks with different units of measurement

Structural steel erection (includes bolting, shimming, connecting, aligning, etc.)

In the 1980s, many project management packages were introduced to the

market. Primavera Project Planner and Microsoft Project are two of such

recognized standard commercial software. These programs provide an

automated means for project tracking and scheduling. However, access to these

softwares was limited to trained personnel working on certain machines in a

specific location (Pena-Mora et al. 2002). So once a project has started with an

original schedule, the actual field data is recorded on paper, email, word

14

processor, or a spreadsheet documents before reaching the scheduler on a

weekly or monthly basis.

Repass et al. (1995) developed a new tool called updater to improve

efficiency and effectiveness of construction schedule updating. It employs

emerging palm-held computer technology to automate processes currently bound

to manual paper-based methods due to incompatibilities between computers and

the harsh construction environment.

Chin et al. (2005) presented a real time 4D CAD + RFID for project

progress managements. The model mainly presented building elements in 3D

CAD models according to as-built progress, where the as-built information is

collected in real-time by sensing the progress throughout the supply chain using

RFID. 4D+RFID aimed at supporting processes with a focus on structural and

curtain wall elements, such as steel columns and beams, concrete slabs, and

curtain walls, which are typically on the critical path of project schedules in high-

rise building construction projects. The process is that RFID is applied to sense

the progress status of ordering, delivery, receiving, and erection of building

elements, and then the as-built progress information is presented in 3D CAD

models.

Poku et al. (2006) developed a system called PMS-GIS (Progress

Monitoring System with Geographical Information Systems) to represent

construction progress not only in terms of a CPM schedule but also in terms of a

graphical representation of the construction that is synchronized with the work

schedule. In PMS-GIS, the architectural design is executed using a computer-

aided drafting (CAD) program (AutoCAD), the work schedule is generated using

a project management software primavera (P3), the design and schedule

information (including percent complete information) are plugged into a GIS

package (ArcViewGIS), and for every update, the system produces a CPM-

generated bar chart alongside a 3D rendering of the project marked for progress.

The GIS-based system developed in this study helps to effectively communicate

the schedule/progress information to the parties involved in the project, because

15

they will be able to see in detail the spatial aspects of the project alongside the

schedule.

Memon et al. (2005) presented a system that integrated Auto CAD and

digital photos to track the progress of construction project. The system proposed

is called Digitalizing Construction Monitoring (DCM) Model. It has made a

practical attempt to automate the process of producing as-built construction

schedule by applying modern photogrammetry techniques to photographs and

integrating with CAD drawings. The applications of DCM model in monitoring the

progress enables project management team to better track and control the

productivity and quality of construction projects.

2.1.1 Technology in Material Tracking

Regardless of the type of project, enough resources must be allocated on

quantity tracking to acquire accurate and timely data that can be used effectively

to control a project and to make progress payment.

In any construction project the cost of materials can exceed half the cost

of construction. Many researches have indicated that in a typical industrial facility

50% to 60% of the total cost is for equipment and materials. The proportion in

terms of cost of materials has increased more than labor. Bernold and Treseler

(1991) stated that costs of materials have increased more than labor and they

pointed out that the construction industry spends 0.15% in material management

systems.

Some studies have shown that an effective material management system

can produce 6% improvement in labor productivity and a computerized system

can produce additional 4 -6% in savings (Stukhart 1995) . Researchers have

acknowledged the importance of materials and the impact that these have in the

total project cost, plan and operations.

The project management team must focus on materials management in

the following stages: Planning, Preliminary design, Final design, Procurement,

Vendor control, Construction, and Closeout. It is a mean of acquiring information

16

about installed quantities at the jobsite, which can then be matched with resource

expenditures such as labor hours, equipment use, etc. (Halpin 1985).

Potential application for materials tracking in commercial construction

include concrete placement operations and steel frame components tracking.

These applications provide viable uses because they offer incremental

improvements over existing methods, reduced labor costs, real-time identification

and tracking and they provide the potential for automatic billing upon receipt of

materials at a jobsite.

Jaselskis et al. (1995) proposed a system using RFID technology to

control concreting operations that would ensure proper delivery, billing, and

quality control for concrete. The process starts when the contractor places an

order with the concrete supplier. The requirements for the concrete mix and the

ID numbers for the assigned trucks would be transmitted to a computer in the

batch plant. Next the RFID tag would be programmed to provide concrete mix

admixtures, time of loading, and delivery location. When the truck arrives at the

jobsites, a scanner would read the RFID tag and communicate by RF link to the

jobsite computer. The RFID tag information would be matched with the electronic

data information from the plant. After the concrete placement is completed, the

concrete truck would again pass the scanner and the delivery completion time

would be transmitted to the concrete supplier to make plans for the next truck. In

the same paper, Jaselskis presented a system to manage critical materials on

the construction site. The system consists of assigning an RFID tag for each

material delivery vehicle. Each package of critical material would also have an

RFID tag. Both the vehicle and package tags would be read at the gate and

recorded on the jobsite computer. The jobsite computer would maintain

databases of materials on hand and their storage location, as well as materials

installed. The saved information was used to trigger payments from the

contractor to suppliers and generate requests for progress payments from the

contractor to the owner (Jaselskis et al. 1995)

Yagi et al. (2005) proposed the concept of parts and packets unified

architecture that allows parts or units to signal change in their attributes as they

17

go through the complex production system. The combination of RFID and glue

logic or active database was proposed as a possible control mechanism, which

achieves the required dynamic equilibrium for construction activity without

hindrance or halt of production at worst. When a chip implanted part passes

through a gate, the gate reads the product URL of the part. It determines what it

is, where it is, when it is, as well as in what state it is. The corresponding data

point in the glue logic is then altered, which generates an event and a chain of

succeeding actions.

Tserng et al. (2005) presented a web-based portal system that

incorporates wireless technology and mobile devices to improve the efficiency

and effectiveness of data acquisition on site and information sharing between

participants to assist the managers to control and monitor the delivery progress

in a construction supply chain delivery. The MConSCM system not only improves

the data acquisition on site efficiency by using automated bar code enabled PDA,

but also provides a monitor to control the construction progress.

2.1.2 Technology in Equipment Tracking

The jobsite productivity of a project involving considerable amount of time

and effort is affected by the selection of the appropriate type and size of

construction equipment. It is therefore important for site managers and

construction planners to be familiar with the characteristics of the major types of

equipment most commonly used in construction. Typically, construction

equipment is used to perform essentially repetitive operations and can be broadly

classified according to two basic functions: (1) operators such as cranes,

graders, etc. which stay within the confines of the construction site, and (2)

haulers such as dump trucks, ready mixed concrete truck, etc. which transport

materials to and from the site (Hendrickson 1998).

Real-time tracking of construction equipment, utilizing the GPS technology

and wireless communications to avoid collisions, offers a multitude of benefits

and can be used for optimizing productivity, in addition to safety and security

18

applications. The technology has applications in both automated as well as

traditional construction sites (Oloufa et al. 2003).

Goodrum et al. developed a prototype tool tracking system to track tools in

a mobile environment and to inventory hand tools that may be located in either

mobile gang boxes or truck boxes. Active RFID technology has significant

potential to improve tool inventory and allocation on a construction jobsite. The

RFID tags have the capability to provide adequate read range and durability

needed for a tool tracking and inventory system research used active RFID tags

in the prototype tool tracking system (Goodrum et al. 2005).

2.2 Computer and Wireless Integrated Construction

Advances in information technology have gradually changed how

construction data are managed in the field. These advances, such as mobile

computers, wireless communications, video conferencing, collaboration systems,

3D laser scanning, digital close range photogrammetry, and sensors have

provided new ways for collecting and managing project information.

Considerable amount of research is being done to remove the

dependency of a person on the desktop computer as the only means of

collaboration and accessing the network, as most projects tend to have a

substantial work force working on site or out of the office where it is not always

possible to have a desktop computer (Pena-Mora et al. 2002).

Some research at Carnegie Mellon University has explored the use of

handheld computing devices in the field for bridge inspection (Garrett et al.

1998). The equipment is non-encumbering and allows the engineer to perform

inspection in a natural manner.

Work at the University of Kent at Canterbury concentrated on examining

the special needs and environment of the field worker, reflecting on the handheld

computing instrument features required for a successful PDA for use in the field.

The research effort also involves development of novel software tools for the

19

mobile field workers but exploit existing handheld computing and sensor

technology (Pascoe 1998).

Liu et al. (1997) proposed the Digital Hard Hat (DHH) technology, which

enables dispersed users to capture and communicate multimedia field data to

collaboratively solve problems, and collect and share information. The DHH is a

pen based personal computer running Windows XP. It is used to collect

multimedia information. Special software called Multimedia Facility Reporting

System allows the field representative to save multimedia information into a

project specific database, which is then accessible to others through the World

Wide Web. The pen-based computer can also be used to communicate between

the construction site and other locations using a direct network connection, a

wireless network connection or any means of cellular communications.

Brilakis (2006) presented a case study on long-range, wireless

communications suitable for data exchange between construction sites and

engineering headquarters. He defined the requirements for a reliable wireless

communications model where common types of electronic construction data will

be exchanged in a fast and efficient manner, and construction site personnel will

be able to interact and share knowledge, information and electronic resources

with the office staff.

Singhvi et al. (2003) developed a context-aware information system

designed to deliver up to-date project information from the main office to the

construction site. The objective was to help the user manage the complexity of

the construction data by proactively tracking current resource requirements and

proactively obtaining access to context-relevant information and services. To

achieve this, the system used off-the-shelf handheld computing devices and an

on-site wireless network for local communication. This allowed continuous

access to data and resources as users moved around the job site. This work

highlighted the benefits of context-aware computing for on-site information

delivery at a construction site and the need for better communication methods.

Tsai et al. (2006) developed a synchronous system integrated with

wireless and speech technologies for on-site data collection. The system was

20

applied in a material management case study, in which construction workers

communicated directly with application devices to achieve synchronous

operations and simplify manual data entry. After the system tests, analytical

results relating to efficiency improvement indicate that the proposed synchronous

system increased productivity, time efficiency and comparative work efficiency

due to the decreased lead processes and operation time.

2.3 Barcode

The use of technology to improve the availability of tools and materials is

not a novel concept. Barcode have a long history of tracking materials not only in

construction but also in other industries. Barcode system components basically

consist of a reader, barcode labels, and printers. Many barcode symbologies are

used in a variety of applications. Each symbology represents the rules for

character encodation, error checking, printing and decoding requirements, and

many other features.

The basic structure of a barcode consists of a leading and trailing quiet zone, a

start pattern, one or more data characters, optionally one or two check

characters and a stop pattern (Figure 2.1).

Figure 2.1 Basic Barcode Structure

Source: (http://www.taltech.com/resources/intro_to_bc/bcbascs.htm)

The most popular ones are the Universal Product Code (UPC), the

European Article Numbering (EAN), Code 39, Interleaved 2 of 5 Code, and Code

128….etc. Code 39 is being used in construction and most construction related

applications (Blakey1990). In general, barcodes can be classified into three main

categories: linear, stacked, and matrix barcodes. Compared to linear barcode,

21

stacked and matrix barcodes have more data capacity and resist damage. More

information is presented in appendix A.

2.3.1 Barcodes Applications in Construction

As explained previously, barcode is an automatic identification solution

that streamlines identification and data acquisition. In the construction industry

barcode has been the point of attraction of a lot of research and it was

documented in some literatures. The application of barcode has been used in

many areas in the construction industry as follows: (1) to identify and find

materials and build components on a construction jobsite (Bell and McCulloch,

1988; Bernold, 1990; Anderson, 1993; Skibniewski and Wooldrige, 1992); (2) to

reduce loss and misidentification of material and equipment. With the utilization

of barcode system, it is possible to track construction assets such as tools and

equipment, identify them electronically, and track their movements. The

warehouse clerk can know where the asset was, and where it is now and, who

has it (Lundberg and Beliveau, 1989); (3) to manage construction equipment on

the jobsite (Wirt et al., 1999); (4) to track workers on the construction site. Some

construction companies are currently using time cards supplied with barcode

labels to access employee information such as the name, work area, and cost

accounting code. Work accomplished is credited to the employee account by

scanning the label on the time card (Bell and McCulloch, 1988); (5) to identify

documentation, drawings, material, equipment, and project activities. A barcode

label can be applied to construction blueprints and important construction

documents. The barcode labels can include data or instructions that enhance the

safety, the quality, and performance of construction activities (Stuckhart and

Cook, 1990; Rasdorf and Herbert, 1989); (6) to integrate barcode and GIS for

monitoring construction progress. Through systematic monitoring of the

construction process and representation of the erection progress, the scheduled

components for erection are repetitively tracked (Cheng and Chen, 2002).

Although an affordable technology, barcodes’ usage in construction

suffers some problems like short range and durability. Barcodes require a line of

22

sight and become unreadable if they are scratched or dirty. Radio Frequency

Identification technology seems to solve all these problems encountered by the

use of barcode.

2.4 RFID

Radio Frequency Identification (RFID) is identified as a part of automatic

identification technologies in which radio frequencies are used to capture and

transmit data. Information is communicated electronically via radio waves and

does not require contact or line-of-sight to transmit stored data; therefore, using

RFID technology for the collection and transfer of information provides one with

an inexpensive and non-labor intensive means of identifying and tracking

products. The RFID tag can contain all pertinent information about the item.

Unlike bar codes, RFID has the ability to offer the possibility of reading, writing,

transmitting, and storing and updating information, identify and track products

and equipment in real-time without contact or line-of-sight and the tags can

withstand harsh, rugged environments. An RFID system is composed of tags,

which carry the data in suitable transponders, and an RFID reader, which

retrieves the data from the tags (CII, 2002).

2.4.1 Tags or Transponder

The word transponder is derived from the two words: TRANSmitter and

resPONDER. The transponder or tag contains an antenna and integrated circuit

ship that is encapsulated to protect against the environment (see figure 2.2).

Tags are programmed with the data that identifies the item to which the tag is

attached. The tag can be either read only, read once/write many, or volatile

read/write. Read only tags are low capacity tags, usually hold approximately 8 to

128 bits of memory and used for identification purposes. In read/write tags, the

user can alter the information on the tag as many times.

23

Figure 2.2 Antenna sealed with RFID tag

There are two classifications of RFID tags: passive and active. The means

in which they receive power for transmission determines their classification.

Passive tags depend on a power source provided by the RFID reader’s energy

field and may have read-write or read-only capabilities, whereas, the active tags

have an internal power source and are rewritable. Passive tags generally have

shorter read ranges but have a life that usually outlasts the object that it is

identifying. Active tags have longer reading ranges, high memory, and better

noise protection. However, these tags are larger and heavier, more expensive,

and have a shorter life (3 – 10 years) than passive tags. Read-only tags are used

for simple identification purposes because they can only store a limited amount

of information that cannot be altered. Such tags may be used to identify a

package of nails or screws because they have many applications and are not

designated to a particular item or activity.

2.4.2 Antenna

The function of the antenna attached to a reader is to transmit an

electromagnetic field that activates a passive tag when it is within reading range.

Once a passive tag is activated it can transmit information from its antenna to

that of the reader where it is processed. During rewriting applications the antenna

of the reader acts as a relay device in the reverse direction, the reader

communicates a message through its antenna, which transfers and stores the

24

new data to the activated transducer via its antenna. The RFID tag’s antenna is

practically maintenance free and can be configured in a variety of shapes and

sizes ranging in size from a grain of rice to the size of a brick (Zebra

Technologies, 2002).

2.4.3 Reader

Reader monitors incoming signals from the transponders to ensure valid

tag data and error free operation. Depending on the applications, readers may be

integrated into handheld computers or they may be stationary and positioned at

strategic points, such as a facility entrance or on an assembly line (Zebra RFID

Passive Tag Reader) (see Figure 2.3). The handheld readers offer portability,

however, the stationary devices offer a larger reading range. As stated above,

readers have an antenna for sending and receiving signals and a processor for

decoding them. The reader receives instructions and information from the

antenna through the scanner, which is a part of the reader that examines analog

output from the antenna. The scanner’s information is then converted into a

digital format by the reader, which the computer or processor can then use for

data analysis, recording, and reporting (CII, 2001). There are readers today that

can simultaneously read 100 to 2000 tags per second.

Figure 2.3 Handheld Stationary Readers

25

2.4.4 RFID Applications in Construction

Radio Frequency Identification technologies provide a wireless means of

communication between objects and readers. RFID has a place in construction

because it provides the industry a potential to improve construction productivity,

quality, safety, and economy, cutting labor and material costs and enhancing

project schedules. There have been quite few publications on RFID research and

applications in construction.

Radio Frequency Identification (RFID) has emerged as a technology that

can be effectively applied for real time measurement of project information in the

construction industry, such as for labor management, safety management,

equipment management, and progress management of various works including

concrete, pipe spools, earthwork, structural steel works, and curtain walls.

Furthermore, it is expected that RFID will improve the limits on progress

management (Jaselski 2003, Yagi 2005, and Song 2005).

The most prominent application of RFID in construction has been its ability

to improve the efficiency of the materials and equipment management process.

In a case study conducted by Bechtel in their $338 million Red Hills Project, time

spent locating and tracking pipe support and hangers was reduced by 30% (CII,

2002).

Rohm & Hass conducted an RFID pilot study that received, identified, and

tracked Honeywell smart instrument installation. Benefits outlined from this case

study can be summarized in inventory shrinkage, decrease of rework costs,

improvement in data integrity (CII, 2001).

Ngai et al. (2005) presented a case study on the development of an RFID

prototype system that is integrated with mobile commerce in a container depot.

They concluded that the system keeps track of the locations of stackers and

containers, provides greater visibility of the operations data, and improves the

control processes.

El-Misalami (2003) proposed a system using RFID to track the activities of

workers and equipment at the construction site. The resulting records were used

to update the cost control system. Each worker would have a read write RFID tag

26

to record his activities. The tag would be approximately the size of a credit card

and could be used as a worker identification badge. The use of equipment would

be tracked by associating the equipment with the operator and the operator’s

activity. The system was adapted for both tool-room checkout and large

equipment management.

RFID can also provide security to construction jobsites. Workers,

operators, and equipment tagged with RFID can record and make certain proper

usage and handling of equipment, materials, and documents. These systems

would also ensure that only qualified equipment operators have the ability to

operate restricted equipment, reducing the likelihood of misuse and accidents

(Durfee 2002).

Song et al. (2006) presented a case study of fabricated pipe spools in

industrial projects. Field tests of current RFID technology were conducted to

determine technical feasibility for automatically identifying and tracking individual

pipe spools in lay down are yards and under shipping portals Potential benefits

found from the use of RFID technology in automated pipe spool tracking may

include (1) reduced time in identifying and locating pipe spools upon receipt and

prior to shipping, (2) more accurate and timely information on shipping, receiving,

and inventory, (3) reduced misplaced pipes and search time, and increased

reliability of pipe fitting schedule.

2.5 Construction Site Information

A construction project is considered as a process that involves many

activities and a large amount of information that are related to each other. During

the construction phase of a project it is essential that good and timely flow of

information prevail throughout the process. A construction project essentially

involves a large amount of information of various types. This is due to the fact

that different parties perform independent tasks on a project to produce a single

final product. Since the design of a project must somehow be communicated to a

lot of parties on the construction site, it is important that clear information,

27

coherent and efficient communication exist to ensure successful work by all

participants in the project. The specifications must be translated into information

that all parties can use in fulfilling their tasks. Hence, the need for drawings,

contracts, specifications, building codes, and other forms of information emerges.

At the same time, the performance of the project must also be communicated

back to management so that it can be controlled effectively. In order to explore

and develop new effective methods of information management on the

construction site, the starting point should be identification of on site construction

information.

2.5.1 Construction Site Information Needs

Information needs in construction have increased as projects have

become more complex and owner demands have become more challenging.

During jobsite project execution, there are three variables which can either hold

back or facilitate successful results, mainly quality, quantity, and timing of

information. The information needs on a construction project have been

extensively documented in the construction IT literature and have been

organized into thirteen major categories from a generic construction project

perspective (Stuckhart and Nomani 1992, de la Garza and Howitt 1998). These

thirteen categories include employee time, attendance, and work tracking;

schedule and resource control; materials management; tool tracking; document

control; drawing control; quality control; equipment management; request for

information (RFI); cost management; jobsite record keeping; submittals; and

safety monitoring. Each category was further divided into more detailed

subcategories. For example, the group of request for information contains the

following seven subcategories: design intent and clarification, subcontractor

information, contract specifications, contract drawings, work package information,

means and methods, and implementation problems. Refer to Appendix A to see

a detailed table of jobsite information needs as presented by De la Garza and

Howitt.

28

Another study performed by Chen and Kamara showed that on site

construction information is grouped into twelve categories including drawings,

material information, equipment information, contract, progress, safety

information, sub-contractor information, design clarification, construction

methods, specification, labor information, and quality information (Chen and

Kamara 2006).

Scott and Assadi summarized sites records into three main categories

which consist of information related to finance, quality, and progress. Especially

the progress records typically kept by contractors and supervisors aim to identify

the project life cycle information consisting of weekly progress reports, day work

sheets, photographs, as-built schedule, and minutes of progress meetings (Scott

and Assadi 1999).

Bowden et al. indicated that the main type of information that the people

onsite deal with is paper based, which constitutes a disadvantage for site

information communication and exchange (Bowden et al. 2004). Lack or

inefficiency of information exchange can result in people on construction site

overlooking important issues that require immediate response and often causes

on site delays and loses in schedule and cost (Singhvi and Terk 2003).

2.5.2 Construction Site Information Users

In addition to information needs on a construction project there are people

who may be considered users as well as sources of information. The following is

a list of eighteen users and suppliers of information presented by Shahid and

Froese: upper management; construction manager; chief engineer; procurement

manager; project manager; project engineer; planning/scheduling engineer; cost

engineer; estimator/quantity surveyor; accountant; purchasing agent; field office

engineer; field engineer; superintendents; foremen; craft worker; laborer

helper/apprentice.

The most effective way for construction people to exchange information on

construction sites is to retrieve or capture information at the point where they

occurred and at the time when they need it. However, this situation is still ideal

29

and can’t be applied with traditional information management methods, relying

mostly on paper-based documents. The next section presents a framework of a

real time model to track the progress of the construction project.

2.6 Survey of Wireless Technologies in Construction

ENR published in 2004 that mobile communication, which is the most

prevailing form of wireless technology, is one of the 10 technology that changed

construction (Sawyer 2004). Wireless technology holds further potential to bring

significant changes to the process operations at the construction sites. However,

it was expected barriers exist to the implementation of the new wireless and

mobile technologies in the construction industry. A survey was conducted by the

ASCE-CI wireless construction committee to identify the current use of wireless

technologies in the construction industry and identify industry’s opinions on

barriers and opportunities (Williams et al. 2006).

2.6.1 Wireless Technologies in Construction

Laptops and Desktop are the top digital tools used in construction. With an

edge slightly less than 90% they overcome phone and still camera (figure 2.4).

Also it was noticed there is a rise in using sensors and tablet PC on the

construction site. PDA percentage is slightly less than 60% and is being used

more than video camera. Usage rate was calculated by adding the scores for one

question and dividing it by the maximum possible score for the same.

Figure 2.4 Digital Hardware Used in the Construction

30

Using another set of questions regarding the use of cutting edge computer

tools and means, CAD percentage was the most used with a percentage of more

than 60%. Video conference, web portal, and e-Learning come in second place

with 42%. RFID and GIS are still underused and have low percentage of less

than 20%. What is surprising is the percentage of barcode which is relatively low

especially that it has been introduced to the construction industry for a while.

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Figure 2.5 Cutting Edge Tools Used in the Construction

2.6.2 Barriers to Wireless Applications in Construction

It appears the respondents did not reach a consensus about the major

barrier to the uses of new technology. Lack of collaboration, high cost, and

insufficient tech support and training are among the primary reasons given for a

reluctance to implement information technologies (Figure 2.6). A main concern

for owners, general managers or any person in charge on job site is the amount

of money to spend in order to get benefit from the technology in question.

Wireless communication is an expensive technology. There are a lot of expenses

to be taken into consideration, and a detailed study should be completed to make

sure that the importance and savings resulting from the usage of this technology

worth the expenses. Some of the costs of investing in wireless technology that

need to be considered are: the purchase of the equipment and software, the

maintenance and upgrading of the hardware, the upgrading and licensing of

31

software, the fee of wireless services providers, the salaries of in-house technical

support personnel, the training of the users (De la Garza & Howitt, 1998).

The typical construction project brings together several disciplines and a

large number of subcontractors that have little incentive for sharing risks. Each

subcontractor is held responsible for their individual work which promotes a low

tolerance for risk within the industry. This prevents technology adoption.

Training and tech support need is another major concern of the

respondents. This lack of expertise may be a sign that use of wireless technology

in construction is still at its early stage. Data security and risk of data loss also

are barriers to its application. Till now, all communication systems are

susceptible to being violated and there is possibility that the information

transmitted being received by undesired users. So the information sent has to be

classified according to importance and how sensible it is so that precautions

would be taken.

Another factor that we can’t overlook is the lack of metrics to assess value

and quantify benefits of applying these technologies.

Figure 2.6 Barriers to Wireless Applications in Construction

32

CHAPTER 3

BACKGROUND

This chapter lays necessary background for the research and includes

necessary information to conduct the research. First a detailed description of

wireless technologies is given, accompanied with identification of different parts

pertaining to this technology. Then a review of the concept of decision-making

and utility theory is presented. That includes an outline about the basics and

assumptions of the utility theory, followed by a description of different techniques

used in multi criteria decision-making. Furthermore, a definition of computer

simulation and its uses in construction is discussed to lay the necessary

background for the coming chapters.

3.1 Wireless Technologies

Wireless services represent a progression of technology, and a new era of

telecommunications, but these services have been used for over a century and

remain synonymous with radio. There are several evolving technologies that

have the ability to improve the efficiency of the construction process. In this

research we are limiting evolving technologies to mobile computing. The concept

of mobile computing has been considered to consist of three major components:

computer, networks and mobile applications (Rebolj and Menzel 2004).

Computers, which can be used indoors, and outdoors by users include table

PCs, all kinds of pocket computers, palmtops and wearable computers.

3.1.1 Mobile Hardware

Primary mobile computing hardware that’s available today for the

construction site application are made up of the following groupings: 1) personal

33

digital assistants, 2) handheld computers, 3) pen tablet/touch PC, 4) rugged

notebook PC, 5) wearable computers/digital hardhats, and 6) digital pens

(COMIT 2005).

3.1.1.1 Personal Digital Assistants

A PDA is a digital organizer. The basic features are a calendar, task list,

and memo pad. They require software designed specifically for PDAs such as

Palm OS or Pocket PC operating systems. Palm and Pocket PC are the two

main rival manufacturers of PDA systems. The feature that eventually made

PDAs more useful tools is the ability to easily synchronize information with

desktop computers. When a PDA is connected to a desktop computer and

synchronized, both pieces of hardware are automatically updated with

information. The more sophisticated PDAs have the capability of performing word

processing functions, spreadsheet and industry specific applications, and provide

e-mail and internet access. The most sophisticated PDAs on the market today

are very powerful tools that may have upwards of 160 megabytes of memory and

400 megahertz processors, integrated wireless connectivity, bluetooth short

range wireless connectivity with other devices, and voice recognition capabilities

(COMIT 2005). They can also be integrated with other technologies such as

digital cameras, GPS, barcodes, and RFID.

3.1.1.2 Handheld Computers

Handheld computers refer to larger devices that have the same basic

functionality of a notebook computer but just in a smaller package. They have

smaller QWERTY style keyboards and smaller screens, and are thus convenient

to carry around, but more difficult to operate and view than notebooks. They

generally run a windows based operating system, have all the same upgrade

options of a sophisticated PDA, and are more powerful.

3.1.1.3 Pen Tablet/Touch PC

Tablet PCs or pen computers have been given this name because they all

have touch screen interfaces that can be manipulated with a pen, also known as

34

a stylus. They are usually made to meet the rugged standards since they are

intended for use in the field. They run on a full desktop operating system that has

been modified for touch screen interface and handwriting recognition. Most tablet

PCs offer all the features available to sophisticated PDAs and handheld

computers, plus some additional features and more power. An average size

tablet PC is about the size of a standard sheet of paper.

3.1.1.4 Rugged Notebooks

Rugged notebooks are simply laptop computers that have been designed

to withstand harsh environments for use in the field. They are quite often used for

mounting on all terrain vehicles that will be exposed to the environment, such as

earth moving equipment or military vehicles. These laptops have all the

capabilities of their non-rugged partners and are generally the same size as the

average to small sized laptops.

3.1.1.5 Wearable Computers/Digital Hardhats

This group of mobile computing devices refers to a network of devices that

can be worn by the user in the field. The general scenario is as follows. The

computing device will be one of the devices described in the previous sections

that can be worn in a vest or jacket. The computer is connected to other devices

such as a head set with microphone and video camera. The computer is

wirelessly integrated to the company server via a local network on site. The

wireless network also allows for conferencing with team members in the office.

The general idea is that you have complete access to relevant data and team

members while at a remote location with almost hands free operation.

3.1.1.6 Digital Pen

Digital pens have the least amount of features and power of all the

computing hardware devices being discussed in this paper. They serve the sole

purpose of electronically recording notes in the field. They solve the double data

entry problem for handwritten notes or memos only; however, they do have the

35

capability to perform this function very efficiently. Digital pens are able to store a

certain amount of standard size sheets of paper depending on the amount of

memory they have. Some of the digital pens researched can store up to 100

standard sheets.

(a) PDA (b) Hand Held Computer (c) Digital Pen

(d) Pen Tablets (e) Digital Hard Hat (f) Notebook

Figure 3.1: Types of Mobile PC’s (COMIT 2005)

3.1.2 Networks

Networks, which can support the connection and communication of mobile

computers with sufficient bandwidth, include all types of wireless networks such

as Wireless Wide Area Networks (WWAN), Wireless Local Area Networks

(WLAN), and satellite networks (COMIT 2005).

36

3.1.2.1 Wireless Wide Area Networks

WWAN covers a much more broad area than wireless LAN. According to

Fisher and Wang, today’s most wireless data links in the U.S takes place across

conventional second generation (2G) personal communication networks. The

transmission speed provided by 2G is up to 20 kbps. With the advent of 3G

networks, communication speed can reach 2 Mbps in fixed applications, although

most commercial deployments offer actual transmission rates closer to 100 kbps

in mobile environments. Although the third generation wireless technology has

not yet been fully implement throughout the world, the world’s leading companies

in this market. Samsung are already laying the groundwork for forth generation

(4G) technology.

3.1.2.2 Wireless Local Area Networks

Wireless Local Area Networks (WLAN) are implemented as an extension

to wired LANs within a building and can provide the final few meters of

connectivity between a wired network and the mobile user. The original

specifications developed for wireless LANs was based on the IEEE 802.11.

Since then, three offshoots that are in wide use have been developed: 802.11a,

802.11b, and 802.11g. 802.11a and 802.11b were developed at the same time.

These two standards use different radio transmission techniques, have different

data rates, and operate under different bands of the radio spectrum. WiFi

Technology is probably the most widely adopted wireless technology for

commercial and home uses (Prasad and Ruggieri, 2003). It represents a full

spectrum of related technology ranging from 802.1a, 802.1b, 802.1g, to the most

recent 802.1n. Many off-shelf products are currently available and have been

used under various working conditions. The setup process and maintenance is

fairly simply with comparatively low cost. However WiFi technology only provides

limited range up to a few hundred yards even with the latest technology and

optional signal boosters. To counter this problem, Wireless Mesh Network

(Wikipedia, 2006) can be formed with peer-to-peer wireless access point to

provide larger coverage. WiMax (IEEE 802.16) (Wikipedia, 2006) is a new

37

wireless technology currently undeveloped. It provides much larger range and

data bandwidth than WiFi does, which enable it transfers data intensive streams

such as videos. With a range up to 30 miles, a WiMax network can cover most

construction sites special cases such as road construction. Some municipals

have been considering using this technology to provide WiMax based wireless

cloud to cover the entire city. WiMax may become available some time in 2007.

There are three physical layers for WLANs: two radio frequency

specifications, and one infrared. WLAN configurations vary from simple,

independent, peer-to-peer connections between a set of PCs, to more complex,

intra building infrastructure networks. There are also point to point and point to

multipoint wireless solutions. In a typical WLAN infrastructure configuration, there

are two basic components:

i) Access Points: An access point/base station connects to a LAN by

means of Ethernet cable. Usually installed in the ceiling, access points receive,

buffer, and transmit data between the WLAN and the wired network

infrastructure. A single access point supports on average twenty users and has a

coverage varying from 20 meters in areas with obstacles (walls, stairways,

elevators) and up to 100 meters in areas with clear line of sight. A building may

require several access points to provide complete coverage and allow users to

roam seamlessly between access points.

ii) Wireless Client Adapter: A wireless adapter connects users via an

access point to the rest of the LAN. A wireless adapter can be a PC card in a

laptop, an ISA or PCI adapter in a desktop computer, or can be fully integrated

within a handheld device.

Bluetooth is a technology specification for small form factor, low cost,

short-range wireless links between mobile PCs, mobile phones, and other

portable handheld devices, and connectivity to the Internet. Bluetooth covers a

range of up to ten meters in the unlicensed 2.4 GHz band. Because 802.11

WLANs also operate in the same band, there are interference issues to consider.

Bluetooth technology and products started being available in 2001, but

38

interoperability seems to be a big problem. By mid 2002, WLANs migrate to the

5GHz band to avoid this problem.

Broadband wireless (BW) is an emerging wireless technology that allows

simultaneous wireless delivery of voice, data, and video. BW is considered a

competing technology with digital subscriber line (DSL). It is generally

implemented in metropolitan areas and requires clear line of sight between the

transmitter and receiving users.

3.1.2.3 Satellites Networks

Satellite-based wireless networks provide an alternative to ground-based

wireless or wired networks. Satellite services, since their onset, have had the

ability to provide limited quality two-way-voice, circuit-switched data, packet

switched data, and paging. Their fundamental advantage is the ability to cover a

widespread area, often-global coverage (De la Garza and Howitt, 1998). It may

be necessary to use a Satellite-based system if no other service is provided in

the area. Like GMS/GPRS, satellite service must be obtained from a wireless

provider. The price of satellite service started out much higher than the other

wireless infrastructure options, but has been steadily dropping and is getting

cheaper every year. In some cases satellite based communications will work out

cheaper than an ordinary mobile telephone service or even a wired line. As

satellite communication devices are becoming ever cheaper and more portable,

many more opportunities to exploit their wire-free capabilities will become

apparent (Web 2, 2004).

Current applications of satellite-based wireless services within the

construction industry include: 1) construction site set-up when there is insufficient

time to get suitable landlines installed quickly, 2) fax, email, Internet and intranet

access, as well as videoconferencing for roving professionals, 3) satellite

payphones for use by employees, 4) rapid download of data for design, analysis,

and project management to pre-empt crisis, avert slippages in schedule and

minimize cost, 5) seamless linking of construction sites into wider information

networks, 6) remote fault diagnostics, 7) remote training facilities, and 8) remote

39

video surveillance. The three main cost elements involved with setting up satellite

service are equipment purchases; service fees; and set up, training and license

fees (Web 2, 2004).

3.1.3 Mobile Applications

Mobile applications with the attributes of context-sensitivity and

personalization can support mobile users’ work processes and enable them to

work together collaboratively and cooperatively in a mobile computing

environment. Based on commercially available products and related research,

mobile applications can be grouped into the following categories: 1) CAD

applications, 2) data capture, and 3) project management.

3.1.3.1 CAD Applications

Construction personnel using mobile devices equipped with mobile CAD

applications can view, mark-up, create, edit and collaborate on 2D/3D AutoCAD

compatible designs and digital blueprints anywhere and at anytime when they

are on construction work sites. Users of mobile CAD applications may contact

anyone who needs the support of drawings and designs in the construction field,

such as engineers, project managers, designers and drafters. Most mobile CAD

applications are compatible with popular mobile devices running Windows CE,

Windows Mobile or Palm Operating Systems. In order to communicate drawing

files with desktop PCs, mobile CAD applications can connect and exchange data

with PCs by using ActiveSync for Windows OS or HotSync for Palm OS.

Example applications include PocketCAD, PowerCAD and ZipCAD.

3.1.3.2 Data Capture Applications

Software developed for data capture purposes encompasses tasks such

as punch lists, timesheets, maintenance inspections, construction progress

reporting, materials tracking reporting, or virtually any form that requires a pen

and clipboard by traditional methods. Data capture software come in two types:

1) task specific, which is developed specifically for one task such as punch lists;

40

or 2) form building software, which can be manipulated to create what ever form

is desired. SHERPA (Ward et al., 2003) is one of the mobile data capture

systems, which enables users to utilize workforce driven mobile computers to

collect real time piling work data in the field through a WLAN.

3.1.3.3 Project Management Applications

Applications in the project administration area provide users with the

capabilities of project and programme management such as construction activity

review, activity monitoring and updating, progress management, risk

management, Microsoft Project file view and update, and material and equipment

management, through their on-hand mobile computers. Available commercial

applications include Primavera Mobile Management, CYtools, and OnSite FDM.

Several programs are available that allow for viewing and updating of Microsoft

Project files on both Palm and Pocket PC devices. They include Project@Hand

by Natra Software for the Palm and CYProject by P.E. Wilson Consulting, LLC

(Williams 2003). Both of these packages allow bar charts to be displayed and

activities updated on site.

3.2 Technology Assessment Methods

In technology selection, decision makers have to consider the various

project implication and benefits/drawbacks of one technology versus another.

Many tangible and intangible criteria are considered while evaluating these

options and to arrive to the best technology that serves their needs.

Complications arise when the alternative technologies under consideration are

new and not enough data is available to effectively evaluate all advantages and

disadvantages. The lack of sufficient historical data constrains a decision maker

to carefully analyze the tangible and intangible impact of the advanced

technology on project performance.

Decision theory is concerned with goal-directed behavior in the presence

of options. When the evaluation problem has multiple dimensions, intuitive

41

judgments may become exceedingly difficult. Utility Function model was

developed to help individual decision maker facing a choice involving uncertainty

about outcomes (Dyer et al. 1992).

The main consideration is how to structure and assess an aggregate utility

function such that:

U (x1, x2, …….. xn) = ƒ [u1(x1), u2(x2), …….. un(xn)], Equation 3.1

Where Ui designates a utility function over single attribute xi

Within construction research, multiple attribute utility theory (MAUT) has

been used to select procurement systems (Chan et al. 2001), contractors

(Cheung and Suen 2002), contractor’s markup (Marzouk and Moselhi 2003),

engineering performance assessment (Georgy et al. 2005), and dewatering

systems (Wang et al. 2002). Others have used MAUT for IT related problems,

such as selecting the appropriate networking technology (Abduh and

Skibniewsky 2003), evaluating the performance of IT solutions (Stewart and

Mohammed 2001) and IT decision making in construction (Elmisalami et al.

2006).

3.2.1 Assumptions and Fundamentals of the Utility Theory

The term utility, according to (Baird 1989), refers to the relative liking on

the part of an evaluator for particular outcomes. Assuming a predefined set of

engineering performance measures, a mathematical function between all

possible outcomes of each individual measure and their corresponding relative

liking to the evaluator could be developed. A multiple attribute utility function

integrates these individual utility functions into a single platform, thus, providing a

collective assessment of engineering performance on a project.

Lifson (1972), Keeney and Raiffa (1976), Howard and Matheson (1977),

and Raiffa and Tversky (1988) described the basics and assumptions of the

utility theory. Von Neu mann and Morgenstern developed six constraints which

they felt were required to give mathematical rigor to the topic of utility theory (Von

Neu mann and Morgenstern 1954). The basic concept is that individual, or

42

organization will display a clear intuition of preference between two events, even

if these events are uncertain. The axioms are the most obvious semantic

constraints on preferences with lotteries. The set of axioms involve some very

complex mathematical proofs that this author feels it is beyond the scope of this

thesis.

The first axiom is that of Orderability: Given any two states, the rational

agent prefers one of them, else the two as equally preferable. The decision

maker possesses a complete ordering of all alternatives available to him.

Second axiom is that of Transitivity: Given any three states, if an agent

prefers A to B and prefers B to C, agent must prefer A to C.

The third axiom is related to Continuity: If some state B is between A and

C in preference, then there is a p for which the rational agent will be indifferent

between state B and the lottery in which A comes with probability p, C with

probability (1-p).

The forth axiom of Substitutability is described as follow: If an agent is

indifferent between two lotteries, A and B, then there is a more complex lottery in

which A can be substituted with B.

The fifth axioms deals with Monotonicity: If an agent prefers A to B, then

the agent must prefer the lottery in which A occurs with a higher probability

Lastly, the six axioms is Decomposability: Compound lotteries can be

reduced to simpler lotteries using the laws of probability.

43

3.2.2 Types of Utility Functions

Traditional multiple attribute utility theory provides a methodology for

selecting from among a set of alternatives in the presence of uncertainty. In this

process, the degree of liking of the various possible decision outcomes is

evaluated and further described by probability density functions (utility functions).

Based on the identified utility functions, the degree of liking for each alternative,

commonly referred to as the expected utility, is calculated and used in the

selection process.

The degree of liking of the various possible decision outcomes is

evaluated and further described by probability density functions. Based on the

identified utility functions, the degree of liking for each alternative, commonly

referred to as the expected utility, is calculated and used in the selection process.

The assessment of a multiple attribute utility function is usually

accomplished by decomposing this function into m single attribute functions.

Each of these single attribute utility functions, Ui(yi), i =1, 2,…..,m, identifies the

degree of liking on the part of the evaluator of the various possible values that

can be associated with attribute i. Among all, two values, UL and UH are of a

particular significance. Typically, UL represents the value where the degree of

liking reaches zero, while UH represents the value where the degree of liking

reaches its ultimate level of 1.0. This can be translated into

Ui (UL) = 0.0 and Ui (UH) = 1.0

Between the two values UL and UH, the degree of liking varies from 0.0 to

1.0. The shape of the utility function Ui(yi), that depicts such change depends on

the evaluator’s risk attitude.

For utility independent attributes, the additive multiple attribute utility

function takes the form

ui(y1, y2, ….., ym) = w1u1(y1) + w2u2(y2) + ...... wmum(ym) Equation 3.2

Where ui(yi) = single attribute utility function for attribute i and ranges from

0.0 to 1.0; yi range of values taken by attribute i ; and wi corresponds to the

relative importance of attribute i.

44

Relative importances are positive numbers that sum up to unity. In

traditional MCDM problems where an alternative needs to be selected, the

expected utility value is calculated for each alternative based on equation 3.2.

Accordingly, the alternatives can be ranked and the alternative with the highest

EU value is then selected

The shape of the utility function ui (yi) identifies the degree of liking on the

part of the evaluator of the various possible values that can be associated with

attribute i. The utility curve may be simply straight line used for risk neutral

attitude, risk aversion, or risk seeking (Georgy 2005). Before finalizing the overall

decision-making process, a utility function (equation) must be fitted for the

decision criterion. The list of applicable standard forms of utility functions (Lifson

and Shaifer 1983) includes three types as shown in figure 3.2:

U(x) = A(1 + eBx )

U(x) = Ax + B

U(x) = A + Bcx

Where,

U(x) = utility value for decision attribute’s level x

X = decision attribute’s level

A, B, c = constants

Figure 3.2: Types of Utility Curves

45

The straight-line function, used for risk neutral attitude, is commonly

employed in practical applications.

3.2.3 Hierarchical Structure of the Multi Attribute Utility Theory

3.2.3.1 Defining evaluation objectives

The evaluation theme in the utility function model is based upon how

much each alternative’s attribute achieves the objective of the comparison. An

objective generally indicates the direction in which we should strive to do better.

Organizing the model in a hierarchical structure is a good way to define different

levels of objectives. The high level objectives represent overall objectives. Then

each high level objective may branch into a number of low level objectives that

are finally defined in terms of alternative attributes (Pitz, 1984).

3.2.3.2 Defining Alternative Attributes

To capture and quantify all that is meant by an objective, several attributes

might be defined under each objective. Attributes represent the lowest level of

the objective hierarchy. Those attributes are the indicators that measure how

each alternative succeeds in meeting the objectives. Because each alternative

should have at least one attribute that is not available in other options, each

alternative must make unique contributions to the evaluation objectives.

However, at some point we will be faced with the proposition that further

achievement on one objective can only be accomplished at the expense of

achievement on the other (Keeney, 1976).

Thompson (1982) recommended limiting the attributes to be analyzed to

15 to 20 attributes. When alternatives have too many important attributes, the

evaluator should focus on the most important ones because the problem with too

many attributes is that they make the analysis cumbersome.

46

3.2.3.3 Attribute Characteristics

It is important that the set of attribute be complete, so that it covers all the

important aspects of the problem; operational, so that it can be meaningfully

used in the analysis; decomposable, so that aspects of the evaluation process

can be simplified by breaking it down into parts; non-redundant, so that double

counting of impacts can be avoided; and minimal, so that the problem dimension

is kept as small as possible (Keeney 1976). Once a satisfactory level of

determining the attributes is reached, the quantification process begins by

defining suitable attribute measures. For example, the cost attribute is measured

in dollars. Unfortunately, not all attribute measures are quantifiable. However,

those non-quantifiable attributes can be defined in a subjective way. An example

of non-quantifiable attributes would be the friendly use of a new technology. The

subjective ratings for this attribute would depend on the personal judgment of the

decision maker (El-Misalami 2001).

3.2.3.4 Assigning Attribute Weights

For each alternative, the aggregate utility value is determined by adding

the product of the multiplication of each single attribute utility with its assigned

weight. Attribute weights reflect the contribution of each attribute in the overall

utility index. Attribute weights are not just measures of importance; they also

reflect the range of variation along the attribute measuring scale. If the range of

variation is very small, the attribute weight diminishes and may exclude the

attribute from the model.

The integration of various measures of engineering performance in the

form of a multiple attribute utility function requires identifying a preference

structure that depicts the relative importance of each measure to the others.

Clemen in 1991 reported on various techniques for developing the preference

structure, including scoring methods, utility based methods, outranking methods,

goal programming, and analytic hierarchy process.

Scoring methods are among the simplest tools for solving multi attribute

decision problems. Given n alternatives and m attributes, the decision maker first

47

assigns weights, wi (i = 1,…, m), to each of the m attributes. In order to assess

these weights, the relative importance of each attribute is determined by the

decision maker on a scale of 1 to 10 or 1 to 100. The next step requires the

decision maker to evaluate how well each of the n alternatives performs with

respect to each of the m attributes. In order to accomplish this, a numerical value

is assigned to indicate the degree to which each alternative achieves each

attribute. The worth of each alternative is then computed using a linear weighted

sum relationship and the alternative with the highest value is selected as the best

option.

In the utility-based methods, the decision maker answers some trade-off

questions to specify the single attribute utility functions, to select the form of the

multi attribute function, and to determine the scaling constants. The primary

advantage of this approach is that the problem becomes a single objective once

the utility function has been assessed correctly, thus ensuring achievement of the

best compromise solution.

Outranking methods are classes of multi criteria decision-making

techniques that provide an ordinal ranking of the alternatives. It allows the

decision maker to choose the alternative that are preferred for most of the criteria

and do not result in an unacceptable level of any one criterion. This approach

examines the non-dominated alternatives and searches for a subset of the non

dominated solutions for which a certain degree of dissension is acceptable to the

decision maker.

Goal programming (GP) can be used only when there exists an explicit

mathematical relationship between decision variables and the objectives and

constraints. GP is a good technique for identifying an acceptable solution when a

minimum acceptable achievement level has been defined for each objective.

The Analytic hierarchy process (AHP) is a multi criteria decision-making

technique that allows the consideration of both objective and subjective factors in

selecting the best alternatives. This approach is used to arrive at a cardinal

ranking of alternatives for multi attribute decision problems.

48

Among all of the possibilities, this study uses the eigenvector prioritization

method, which is commonly employed in the AHP developed by Saaty (1980).

This method is a popular alternative for deriving the preference structure in

various practical applications of MCDM (Zeleny 1982; Mollaghasemi and Pet-

Edwards 1997). The major strengths this method brings are its systematic

procedure and its ability to examine the consistency of the evaluator’s judgments.

3.2.4 Analytical Hierarchy Process

The analytical hierarchy process (AHP) has found a wide application in

various decision problem such as conflict resolution, technological problems, and

economic problems (Vargas 1990; Abourizk et al. 1995; Saaty 1988). This

evaluation process has been defined as a theory of measurement with a capacity

to handle both tangible and intangible sets of criteria. AHP incorporates

judgments and personal values in a logical way. It allows the consideration of

both objective and subjective factors in selecting the best alternative. AHP allows

the user to establish criteria for decision-making in a hierarchy and analyzes

complex decision problem. The importance of establishing a hierarchy in a

decision problem is to properly account for the various factors involved in the

decision making process and establish their interdependencies. Although it is

important that a hierarchy should represent all major criteria and subcriteria, it is

not necessary for the hierarchy to be exhaustive. AHP is based on three

principles: decomposition, comparative judgments, and synthesis of priorities.

The decomposition principle requires that the decision problem be

decomposed into hierarchy that captures the important elements of the problem.

Higher elements in the hierarchy are more general goals and objectives, lower

elements in the hierarchy are more specific attributes, and the lowest levels are

the alternatives. Each level must be linked to the next higher level, and adjacent

elements within one level must not be too disparate.

The principle of comparative judgments requires assessments of pairwise

comparisons (on a scale of relative importance) of the elements within a given

level, with respect to their parent in the next higher level. These assessments are

49

collected into comparison matrices where each entry in the matrix belongs to the

relative importance scale used in the comparisons. The entries in the matrix are

then used to generate a derived ratio scale that reflects the local priorities of the

elements in the hierarchy.

The synthesis of priorities principle takes each of the derived ratio scale

local priorities in the various levels of the hierarchy and constructs a composite

set of priorities for the elements at the lowest level of the hierarchy.

3.2.4.1 Setting Priorities

The first step in establishing the priorities of elements in a decision

problem is to make pairwise comparisons, which mean that the elements in pairs

are compared against a given criterion. For pairwise comparisons a matrix is the

preferred form. To begin the pairwise comparison process, a matrix A = (aij)

where i, j = 1…n, is established for evaluation of criteria and each criterion, ai, is

compared with another criteria aj. Start at the top of the hierarchy to select the

criterion C that will be used for making the first comparison. Then from the level

immediately below, take the elements to be compared: A1, A2, A3 and so on as

shown in figure 3.3.

C A 1 A 2 A 3

A 1 a 1 1 a 1 2 a 1 3

A = (a ij) = A 2 1 / a 1 2 a 2 2 a 2 3

A 3 1 / a 1 3 1 / a 2 3 a 3 3

Figure 3.3 Sample Comparison Matrix

3.2.4.2 Pairwise Comparison Scale

To fill in the matrix, we use numbers to represent the relative importance

of one element over another with respect to the criteria. It is important to use a

relative scale that has been predetermined rather than using a standard scale

because of the intangible nature of the criteria involved. The importance of once

criterion over the other is established by using a predetermined scale (Saaty

1988) as shown in table 3.1.

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Table 3.1 Pairwise Comparison Scale presented by Saaty

Degree of

Importance

Definition Explanation

1 Equal importance Two elements contribute equally to the property

3 Moderate importance Experience and judgment slightly favor one element over another

5 Strong importance Experience and judgment strongly favor one element over another

7 Very strong importance An element is strongly favored and its dominance is demonstrated in practice

9 Extreme importance The evidence favoring one element over another is of the highest possible order of affirmation

2,4,6,8 Intermediate values between two adjacent degrees of importance

Compromise is need between two judgments

3.2.4.3 Eigenvector Prioritization Method

Using this matrix, the local priorities are determined by calculating the

normalized principal eigenvector [W]3*1, corresponding to the dominant

eigenvalue (max.

Mollaghasemi and Pet Edwards (1997) describe the process of calculating

the eigenvector of the matrix [Anorm]3*3. First the matrix is normalized by dividing

the values of each column on the sum of the column as shown in figure 3.4.

a11 a12 a13

a11+ a21+ a31 a12+ a22+ a32 a13+ a23+ a33

a21 a22 a23

[Anorm]3*3 = a11+ a21+ a31 a12+ a22+ a32 a13+ a23+ a33 =

a31 a32 a33

a11+ a21+ a31 a12+ a22+ a32 a13+ a23+ a33

A23

A33

A11 A12 A13

A21 A22

A31 A32

Figure 3.4 Normalized Matrix

51

Afterwards, elements of the eigenvector are calculated as the average of

each individual row of the normalized matrix as shown in figure 3.5.

A11 + A12 + A13

3

[W]3*1 = = A21 + A22 + A23

3

A31 + A32 + A33

3

W1

W2

W3

Figure 3.5 Eigenvector Matrix

The dominant eigenvalue (max is estimated by multiplying the comparison

matrix [A]3*3 with the calculated eigenvector [W3*1] to produce [AW] 3*1 as shown

in figure 3.6

[AW]3*1 = [A] 3*3. [W3*1] Equation 3.3

[AW] 3*1 = = .

A31 A32

aw1

aw2

aw3

A22

A11 A12

A21

A33

W1

W2

W3

A13

A23

Figure 3.6 Transition Matrix

Then the matrix dominant eigenvalue is calculated as follows:

(max = (1/n) ) (awi / wi) Equation 3.4

One of the important features of AHP is its ability to provide a measure for

the consistency of the evaluator’s judgment. The AHP measures this consistency

or inconsistency through the use of the consistency ratio (CR), which is a

function of comparison matrix dimension (n*n), a random index (RI), and the

dominant eigenvalue (max.

Consistency Ratio (CR) = CI / RI Equation 3.5

Consistency Index (CI) = ((max –n) / (n-1) Equation 3.6

52

The RI for various matrix sizes n has been approximated by Saaty (1980)

based on simulation run as shown in table 3.2.

Table 3.2 Approximated Random Indices RI (data from Saaty 1980) n 1 2 3 4 5 6 7 8 9 10 …

RI 0.00 0.00 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 …

Empirical studies conducted by Saaty have indicated that a deviation in

consistency ratio of less than 10% is acceptable without adversely affecting the

results (Saaty 1980; Lafond 1988). If the consistency ratio for a matrix is greater

than 0.1 then, either the values in the matrix should be rejected or else, steps

should be taken to modify the pairwise comparisons till an acceptable

consistency ratio is obtained.

At every level in the hierarchy, a similar pairwise analysis is conducted for

each subcriteria alternative of that level. For each criterion of the preceding level,

a pairwise comparison is performed between all the subcriteria related to it in the

next lower level.

The comparison matrices are evaluated to establish the priority vectors,

i.e., eigen vectors corresponding to the maximum eigenvalues (max. These

priority vectors are weighted by multiplying them with the weight of the

corresponding criteria from the preceding level, thus defining weighted priority

vectors. Similar procedure is employed at each level of the hierarchy.

Aggregate vectors are computed by adding the weighted priority vectors

obtained at the last level in the hierarchy i.e., the alternative level with respect to

each criterion. An aggregate matrix is defined with the rows formed by the

aggregate vectors obtained in the previous step. The final priority vector is

computed by adding the column entries of the aggregate matrix. The final priority

vector defines the preference among the alternatives with respect to all the

criteria and subcriteria.

53

3.3 Computer Construction Simulation

Simulation is an important feature in engineering because it involved many

processes. It gained a lot of importance since the development of computers.

Computer simulation is a valuable management tool that is well suited to

the study of resource-driven construction operations.

In daily construction practice, construction designers make decisions

regarding complex construction processes. These decisions include construction

methods, selecting equipment, and planning operations. In some situations,

decisions are made with unexpected outcomes. This is because of the

complexity of the operations or the difficulty in visualizing all the processes

involved. In real life, testing a construction method is very expensive and time

consuming. However, simulation is a convenient technique to model “real-life”

construction operations.

3.3.1 General Modeling and Simulation Systems

General modeling and simulation systems are commonly used in

manufacturing and other industries. The uses of general modeling and simulation

languages in construction are demonstrated with models for equipment selection

(Teicholz, 1963), for the estimation of project durations (Carr, 1979), and for the

evaluation of resource allocation strategies (Moura, 1986).

Simulation systems can adopt one of several approaches or strategies.

Three simulation strategies are commonly recognized: event scheduling (ES),

activity scanning (AS), and process interaction (PI) (Martinez, 1996). In

manufacturing and other industries, the PI strategy combined with ES or AS is

very effective in modeling systems because entities that move have many

attributes that differentiate them; and the machines or resources that serve the

entities have a few attributes, and don’t interact too much. Examples of general

modeling and simulation systems are Petri Nets, GPSS, HOCUS, SIMAN,

QGERT, SIMSCRIPT, SIGMA, ITHINK, and SLAMII (Damrianant, 1998).

54

3.3.1.1 GPSS

GPSS (General Purpose Simulation System) is a simulation modeling

language that was developed in the early 1960’s by IBM. GPSS is oriented

toward queuing systems. A GPSS simulation consists of temporary transactions

and permanent facilities, which flow around a network of block diagrams. These

transactions are created and destroyed as the simulation proceeds and which

move through various GPSS blocks. There are about 40 standard building blocks

in GPSS. Facilities are used to represent the resources needed by the

transactions at the nodes of the network (Damrianant, 1998). The most recent

version of GPSS is GPSS/World (Schriber, 1994).

GPSS/World employs a set of new GPSS Blocks and commands, which

support input/output, rescheduling, continuous and mixed modeling and multiple

data types that include integer, real, and string objects. Also, GPSS World

includes an embedded programming language called PLUS. PLUS language

consists of only a few statement types that can be used just about anywhere

within the simulation, including GPSS Blocks. This feature improved the flow of

simulations. Several new GPSS Blocks have been added to GPSS World. The

new blocks such as, OPEN, CLOSE, READ, WRITE, and SEEK Blocks provided

a powerful interface to programs written in other languages.

3.3.1.2 HOCUS

HOCUS (Hand Or Computer Universal Simulator) (Hills, 1971), developed

in the early 1960’s, enhanced and popularized the concept of activity cycle

diagrams. A HOCUS activity cycle diagram consists of two kinds of nodes:

queues (circles) and activities (boxes) connected by arrows. HOCUS could be

used for both discrete and continuous process modeling. It has been used for

numerous large-scale simulations in several industries in Europe (Poole and

Szymankiewicz, 1977).

55

3.3.1.3 ITHINK

ITHINK is a commercial computational package that has been developed

for modeling system dynamics. ITHINK provides friendly user interface and

animation and it can be used to model discrete systems, such as in construction

(Paulson, 1985). However, its modeling methodology is difficult to use and

understand when it comes to modeling discrete systems (Damrianant, 1998).

3.3.1.4 SLAMII

SLAM (Simulation Language for Alternative Modeling) was developed in

1979 as a commercial simulation language (Schriber, 1994). SLAMII was

designed in 1981 as an enhancement to SLAM. SLAM and SLAMII allow

modeling in a network form. SLAMII is a high-level simulation language with

FORTRAN and C versions that can model complicated applications. SLAMII

network models can be built, animated, and run by using another computer

program named SLAMSYSTEM.

3.3.2 Construction Simulation Using Networks

All construction process simulation tools are based on activity cyclic

diagrams (ACDs) and on activity scanning (AS) simulation strategies. For the

past two decades, researchers have recognized the need to use computer

simulation to plan and analyze construction operations and activities.

Consequently, research in construction simulation and modeling has been

actively carried out, especially in academia.

3.3.2.1 CYCLONE (Cyclic Operations Network)

Interest in simulation applications in construction has been growing since

the introduction of the Cyclone methodology in 1973 (Ioannou 1990). CYCLONE

(Cyclic Operations Network) is one of the first and best known simulation

languages specifically designed to investigate the use of simulation networks for

modeling construction operations and activities is (Halpin, 1973, 1977). The

CYCLONE system has been used frequently to model construction processes.

56

This frequent use is due to the ability to provide a quantitative way of viewing,

planning, analyzing, and controlling the processes and operations (Halpin and

Riggs, 1992). It has been successfully used in modeling construction processes

such as concrete batch plant (Lluch and Halpin, 1982), tunneling (Touran and

Asai, 1987), and modeling construction resources and resolving construction

disputes (AbouRizk et al., 1992, and AbouRizk and Mohamed, 2000).

The Cyclone modeling methodology is a well established, widely used,

and simple methodology that is easy to learn and is effective for modeling

construction operations (Zayed et al. 2000). Among the six building blocks in the

Cyclone modeling methodology, both the Normal and the Combo elements

denote a work task within a process, but the former is used in a non-constrained

situation and the latter in a constrained one. The Queue element denotes the idle

state of a resource entity. Consolidation is a function used to consolidate flow

units at certain points in the system. The purpose of a Counter is to count the

number of times a key unit passes a particular control point in the network model

so that production can be measured. Finally, an Arc is a directional flow between

elements, which is used to model the resource entity's flow direction from node to

node.

MicroCYCLONE is a microcomputer-based program designed to run

CYCLONE simulation models. Before running the simulation, the graphical model

network should be converted into a numerical model using a specialized POL

(Problem-Oriented Language).

Many researchers have used CYCLONE as a base to build their

simulation systems such as Insight (Paulson et al., 1987), UM-CYCLONE

(Ioannou, 1989), Micro-CYCLONE (Lluch and Halpin, 1982), and

STROBOSCOPE (Martinez, 1996).

3.3.2.2 RESQUE

RESQUE is an acronym for RESource based QUEuing network simulation

system (Chang, 1986). RESQUE was designed as a significant enhancement to

57

Cyclone, where the model is not limited to the information conveyed by the

network.

3.3.2.3 COOPS

COOPS is an acronym for Construction Object Oriented Process

Simulation system (Liu, 1991). It is an extension and enhancement to CYCLONE

that was designed and implemented using an object oriented programming

language.

3.3.2.4 CIPROS

CIPROS is an acronym for Construction Integrated PROject and process

planning Simulation system (Tommelein et al., 1994). CIPROS is both a process

level and a project-planning tool. It contains an expandable knowledge base of

construction techniques and methods and makes extensive use of hierarchical

object-oriented representation of resources and their properties.

3.3.2.5 STROBOSCOPE

Stroboscope (State and ResOurce Based Simulation of Construction

ProcEsses) is a general-purpose simulation programming language specifically

designed to model construction operations (Martinez, 1996). It is based on

activity cycle diagrams (ACDs) and the activity scanning (AS) simulation

paradigm.

Stroboscope modeling elements have attributes, defined through

programming statements, which define how they behave throughout a simulation.

Resources in Stroboscope can be bulk or discrete, depending on their type. Bulk

resources represent entities that are not individual and cannot be uniquely

identified, such as sand, water, etc.

Discrete resources represent unique individual entities, such as a specific

truck, particular concrete block, etc. What mainly differentiate Stroboscope from

other simulation tools resides in its simulation language and its open design. Its

simulation language represents resources as objects that have assignable,

58

persistent, and dynamic properties and can actively and dynamically take into

consideration the state of the simulation process (Martinez, 1996).

Stroboscope’s open design allows the user to determine the input and

output at two levels. The first level uses Stroboscope’s built-in programmability

language. The second level extends Stroboscope through dynamic link libraries

created with high level languages: C and C++ (Martinez, 1996).

Stroboscope includes an optional Graphical User Interface (GUI) hosted

under Visio 3.0 or later version. Stroboscope also has some of the characteristics

that general-purpose programming languages have such as, built-in logarithmic

and trigonometric functions, conventional variables and arrays, and structured

flow control with if-elseif-else-endif blocks.

59

CHAPTER 4

REAL-TIME PROJECT PROGRESS TRACKING MODEL

This chapter presents a framework for real time construction project

progress tracking model. After identifying the computer hardware, software,

wireless communication and smart chips that constitutes the basic component of

the model, a detailed step to implement the system in construction is presented.

Then a description of the database that will hold the information is presented.

This database will act as a storage room and a bridge at the same time. It will link

the information sent from the construction site to the project schedule software.

Then the schedule will be automatically updated. At the same time the database

will allow the users to access information and retrieve drawings when needed.

4.1 Framework for Real Time Construction Project Progress Tracking

Based on chapter 2 and the information needed on the construction site,

this research try to integrate different automated data acquisition technologies to

collect data on construction sites, send the information through wireless

connection to a central database where it will be stored, and then use these

information to update the schedule and project progress instantly as soon as the

activities occur. The objective of the model presented is to track the quantity of

materials and equipment usage on the construction site in real-time fashion, and

be able to calculate the percentage complete of the activities based on the

tracking information. In addition to that, the model has another objective, which is

to link the independent islands of communication on the construction site, by

making information in the database available for corresponding users like

erection drawing for example (Ghanem et al. 2006).

60

As shown in figure 4.1, the framework of the real-time project tracking

model is divided into three modules. Two input modules and one output module.

The first part of the framework is related to the construction site.

Resources, composed of materials, labors and equipments, are tagged with

RFID tags. Site engineer and foremen are provided with RFID readers and

PDAs. These are the constituents of the system on the construction site. RFID

tags are scanned using the readers and information are sent to the central

database located at the office. In case needed on the construction site,

information is extracted from the database using mobile device.

Figure 4.1 Model Framework

The second part of the framework is related to the office. A central

database located on the server of the company is located in the office. This

61

database is accessed from a work station. Construction and site office are linked

together using wireless network. Wireless network ensures dual ways of

communication. Information is sent to the database to be accessed by people off-

site, and people on construction site can access information stored in the

database.

The third part of the framework is the output. Updating the schedule

instantly allows the user to track the progress of the project and to conduct

analysis such as earned value analysis to get an objective measurement of how

much work has been accomplished on the project.

4.2 Hardware and Software Alternatives

The constituent objective of this model include (1) a wireless construction

site to ease mobility and network previously stand alone islands of

communication on a job site; (2) a hardware computing system; and (3) an

integrated Radio Frequency Identification to increase the efficiency and accuracy

of the job site data collection. The data needed for integrated cost and schedule

control must be identified, organized and stored in a relational database

management system. The softwares used in this analysis are products of

Microsoft because of the compatibility between Microsoft Project (MP) and

Microsoft Access (MA). Data stored in that model include project activities, which

have a cost account code to facilitate the link between MP and MA.

4.2.1 Hardware Selection

4.2.1.1 Computer Alternatives

Due to the harsh nature of a construction site, it was decided that the

mobile device must meet some rugged standards. The Ingress Protection (IP)

rating should be at least IP54 (Singletary 2006). This rating ensures that the

computer enclosure will stand up against wind-blown dust and rain. The

computer should be able to withstand the drop test from at least three feet to

62

allow repeated droppings while carrying it across the site. A drop test rating of

four feet is preferable, since this would allow repeated droppings from the chest

of an average height person. The computer display should be rated as sunlight-

readable, since it will often be used in direct sunlight. The mobile device must

support wireless networking options, which is not a problem for just about any

mobile device on the market today. The battery system must allow for at least

eight hours of normal operation to accommodate the average workday. Most

devices include a “hotswap-capable” option to allow switching out batteries while

the device is in use. This option combined with purchase of an extra battery

suffices for most battery types and mobile devices. Tablet computers were

deemed more appropriate than notebook computers for use on a construction

site where the user is most often standing up and walking the site.

Notebook computers are almost always heavier and have keyboards that

require two free hands to manipulate efficiently. The rugged notebooks are also

more expensive. Cost quotes and computer specifications were obtained through

websites and by consulting with various rugged computer manufacturers and

authorized resellers over the phone.

Table 5.10 gives a comparison of some of the rugged mobile devices

researched based on price and the requirements mentioned. The tablet computer

chosen to base the analysis on is the iX104C2V model manufactured by Xplore.

This model is moderately priced for rugged tablets and more rugged than most

with an IP 67 rating and drop test of four feet.

Field Manager could be equally accommodated on a handheld computer

or a PDA. The handheld computers are generally more highly priced. They do

have a slightly larger screen, but the difference was determined to be

insignificant. The rugged Recon PDA distributed by Rugged Notebooks was

selected for the analysis. It is priced comparably to some other rugged PDAs,

and like the tablet chosen is very rugged with an IP 67 rating and drop test of four

feet. For both the tablet and the PDA, cameras were selected as an add-on to

allow each user to communicate issues arising in the field more effectively.

63

Table 4.1 Rugged Mobile Device Comparison

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64

4.2.1.2 Wireless Infrastructure Alternatives

Cost quotes and specifications were gathered from wireless infrastructure

manufacturers and resellers through websites and phone conversations. The

802.11b WLAN equipment needed for the implementation consists of access

points (APs) with protective enclosures and omni-directional antennas.

The Orinoco AP-4000 was the access point chosen, along with 5dBi omni-

directional antennas. It was estimated that 2 APs and four antennas would

sufficiently provide wireless access to the project site. These APs cover the 2.4

to 2.5 GHz frequency band. Range boundaries characterize the circumference of

the radio cell that the access point produces (Web 1, 2006). The maximum

outdoor signal range (in the ideal wide-open situation) for this frequency band is

said to be between 1000 and 1500 feet outdoors. The indoor maximum range is

between 200 and 300 feet. One of the wireless provider representatives that

were consulted with claimed that the addition of an omni-directional antenna

could increase an AP’s range by 60%. Connectivity indicates the point at which a

device can associate with an AP at a specific data rate. The 802.11b standard

has a maximum data rate of 11Mbps. As the device moves away from the access

point, the data rate will drop from 11 to 5.5 to 2 to 1Mbps to no connectivity. A

data rate of 1Mbps is still relatively high and should be capable of supporting the

data transfer needed for this application.

The overall performance of the WLAN will be affected by interference and

number of users. A WLAN used on a construction site will have ever-changing

interference due to changing site conditions and equipment usage as the project

progresses. This application is considering only seven users of the WLAN, which

is extremely low and would not present a problem. The only way to truly know the

optimum number and location of APs on site is to perform a site survey. A

wireless specialist could be hired to do this, or the users themselves could test

the network by walking the site with their mobile device. The connectivity and

performance (based on ratio of packets sent to packets received) can be

checked this way. The LCC analysis includes the cost of bringing a wireless

consultant out to the site every three months to perform this service.

65

The price range of APs is approximately between $500 and $900. The AP

chosen has a price of $527. The Symbol AP-4131was quoted at $670 by a

Symbol reseller; therefore, the AP chosen is reasonably priced.

Cellular service providers were contacted to gather information for the two

alternatives using wireless subscriptions. T-Mobile and Cingular were contacted

for price quotes on unlimited data-usage plans for both PDAs and tablet

computers.

4.2.1.3 Smart Chips Alternatives

Cost quotes and specifications were gathered from smart chips

manufacturers and resellers through websites and phone conversations (Web 3

and 4 2006). The smart chips system needed on the construction site consisted

of a reader and an antenna to increase the range of connection. In addition to

that a search for different kind of tags and their specification was conducted.

After doing the search and comparison between different website and from

manufacturers’ feedback, IP4 was chosen as a reader. The IP4 delivers first-of-

its-kind capability by combining the power of a handheld mobile computing

device equipped with PAN, LAN and WAN radios. Users of the 700 Series Color

mobile computers have posted productivity gains and enjoyed application

flexibility enabled by the three radios personal area (PAN) or Bluetooth, local

area (LAN) and wide area (WAN) as well as the area and linear imagers

integrated into the handheld device. Combining those capabilities with the IP4

and the strength of the Microsoft Pocket PC platform gives users a high

performance mobile RFID solution.

The UHF large rigid RFID tags produced by Intermec were chosen as our

passive tags. It delivers superior performance on a variety of surfaces including

plastic, wood and metal. It exists in rugged shape designed for harsh industrial

applications and temperatures. According to the manufacturer no other tag on

the market can claim the ruggedness and worldwide usability of these tags (Web

5 and 6 2006). Pricing for tags is about $4 for a rigid tag and label inserts get

66

down to 15 cents per label. Appendix C has a description and specifications of

the equipment used as per the manufacturer publication.

4.2.2 Software Available

Microsoft Project (MP) was selected for all alternatives as the project

management software for the following reasons: (1) MP has integrated Earned

Value Management functions, and (2) MP is a Microsoft product and it is

compatible with other Microsoft product. Plus it has proven capabilities at

reasonable prices. MP 2003 was used in this study. It goes along with Microsoft

Access 2003, which was used to construct the database.

PocketCAD PRO 4.0 was also selected to include in the analysis. This

selection goes under the assumption that AutoCAD is already the computer

drawing tool being used by the company. At a relatively cheap price of $200 per

copy, this addition can be very beneficial by allowing drawings to be accessed

and manipulated for any purpose.

4.3 Implementation Steps

Each equipment or material has an ID that is connected to a certain

activity in the Master schedule. When the activity starts, the equipment and

materials are scanned with a precise message that specifies the status of the

activity. The activity can also be called by opening a scroll bar where all activities

are listed. Information regarding resource consumption is acquired and entered

by scanning the tags associated with these resources and data related to the

quantity or hour usage are directly entered. At the same time information related

to the installation procedure of the materials under study can be acquired from

the database system. Each worker has an ID card when scanned, data pertinent

to his working hours and the activity he is working on is entered. All these

information are sent instantly as soon it is entered to the database server,

through the wireless connectivity available on the construction site. All activities

have cost account codes to easily relate data to these activities. The process of

67

data exchange is highlighted in figure 4.2 where the users have access to both

planned data files and actual activities that will help to conduct earned value

analysis and monitor the performance of the entire project.

Figure 4.2 Data Exchange and Reporting

Individual objects scheduled for arrival on the construction site are tagged

at the vendor factory using radio frequency identification tags. The encoded

information is scanned directly into a portable computer and wirelessly relayed to

a remote project database. This database has dual functions. A database query

returns graphical representations (e.g. computer aided design CAD) like where to

install the materials and the method used for installation. The second function of

the database is to relate the materials to the corresponding activities in the

project schedule. Based on the amount of installed materials on the construction

site and the related activity, BCWP and ACWP are updated. In turn the schedule

will implement the changes automatically every time information is recorded in

the PDA and sent through the wireless connection to the database.

The same logic is applied to the equipment on the construction site. The

activities that involve only equipment work, like excavation and hauling, are

tracked through the number of hours these equipments are used. Based on the

productivity of the crew and machines, the quantity of work to be done, and the

68

total number of hours, BCWP and ACWP can be updated. Figure 4.3 represents

the general system configuration.

Although the system logic was presented, there are some obstacles to

overcome. The main ones are how to define the percent complete for each work

item, and how to relate different tag categories (equipment, worker, materials) to

each other.

This research is just limited to materials usage, especially the steel parts

because of the limited data available, and both case studies presented to the

author were a pre engineered construction site. But the same logic and database

constructed for steel construction can be applied to other materials and other

resources in general.

Figure 4.3 General System Configuration

69

4.3.1 Work Progress Measurement

As mentioned in table 2.1 in chapter 2, based on the activity under

investigation, there exist 6 different types of measurement method. In our study,

we are concerned with steel construction, pre-engineered and fabricated part. So

the suitable two methods for our case studies are either units completed or

weighted or equivalent unit.

In the next section, we attempt to present a database where all the

information will be stored. This database will have a dual function to store

information, update schedule, keep users informed of all activities, and at the

same time retrieve information.

4.4 Construction of Data Management System

A database with single point of access to all data relating to the

construction site is used in this model. The intention is that this will encounter the

problems caused by duplicate or incomplete paper-based information on site and

also eliminate the need for user to carry bulky paper documentation. The

database also allows all users having access to all of the construction data

captured by other personnel. This allows for the free use of information between

users removing the burden of collating revised construction information caused

by unplanned sequence changes or schedule changes.

So a database management system (DBMS) is essential in supporting

project tracking and control functions. A database provides a platform to

organize, store and retrieve the planned and actual performance data of projects

in a logical and efficient manner. The DBMS queries the stored project data using

SQL (structured query language) to generate different management reports for

control purposes. It follows that the design of the database should follow a well-

defined structure to support the tracking and control of individual tasks at

different levels of reporting. The data structure should also facilitate the linkage of

those individual tasks to their respective construction trades.

70

The system is shown in figure 4.4. The user interface provides

viewing/input window that allows user to interact with the system through the

worldwide web using an Internet browser. The queries component performs the

necessary steps to satisfy the user need. The project database stores the original

information and it’s updated on a continuous basis. Upon completion of the

project, all information collected in the project database can be transferred to a

historical database. Java script functions, Visual Basic-Script functions, and

HTML can be used to design the set of web-forms to facilitate data entry and

retrieve. This research just focuses on the construction of the database part.

Web development, Java Server Pages and Java Script technologies to transform

the Internet into a user friendly interface are not within the scope of this research.

Figure 4.4 Database Management System

4.4.1 Data Dictionary

A data dictionary was created to specify the name, definition, and other

necessary attributes of each data element subjected to standardized data

exchange. It was limited to the following four major aspects of structural steel

71

erection process: 1) tracking status for each pre-engineered building element, 2)

locating and identifying the mark of each steel element at the lay down area to

determine erection sequence, 3) positioning each engineered steel element at

the final position area, and 4) updating the schedule once the activity is done.

Table 4.2 presents the dictionary definition for the categories and

subcategories used in the database.

Table 4.2 Database Dictionary Class Name Data

Element

Definition Type of

Data

Units Data Format

Identification

number

Product identity

number to help

identity members

on jobsite

Text N/A XXXX

Section

number

Order in which a

section of the

structural steel

frame will be

erected

Text N/A XX

Load number

Number of a

group steel

components

delivered by the

truck

Text N/A XX

Structural

Steel Number

Information

Sequence

number

Sequence in

which parts are to

be assembled

during erection

Text N/A XX

Identification

number

Product identity

number to help

identify member

on the jobsite

Text N/A XXXX

Erection

Characteristic Orientation

mark

Orientation in

which parts are to

be assembled

during erection

Text N/A X

72

Table 4.2 Continued Class Name Data

Element

Definition Type of

Data

Units Data Format

Section

number

Order in which

section of

structural steel

frame will be

erected

Text N/A XX

Field date Date which erector

ask materials to be

delivered

Date/time dd-mm-yy N/A

Delivery

Request

Factory

delivery date

Date which factory

expects materials

to be delivered

Date/time dd-mm-yy N/A

Identification

number

Product identity

number to help

identify members

on jobsite

Text N/A XXXX

Erection start

Date which erector

start erection of

steel parts

Date/time dd-mm-yy N/A

Erection

status

Erection

completed

Date which erector

finish erection of

steel parts

Date/time dd-mm-yy N/A

Section

number

Order in which

section of the steel

frame will be

fabricated

Text N/A XX

Fabrication

start

Date which

fabricator start to

fabricate parts

Date/time dd-mm-yy N/A

Fabrication

Status

Fabrication

completed

Date which

fabricator finish to

fabricate parts

Date/time dd-mm-yy N/A

Delivery

start

Date which steel

fabricator start to

deliver steel parts

Date/time dd-mm-yy N/A Delivery

Status

Delivery

Completed

Date which steel

fabricator finish to

deliver steel parts

Date/time dd-mm-yy N/A

RFID Identification

number

Product identity

number to help

identify members

on jobsite

Text N/A XXXX

73

4.4.2 Project Database

A binary relationship is used in designing the database. Relationship types

involve one-to-one (1:1), one-to-many (1: M), and many-to-many (M: N)

relationships. Different types of attributes are used in the development of this

database, including composite, single-valued, multi-valued, null-valued, and key

attributes. Composite attributes form a hierarchy that decomposes a unit into

smaller components, each with its own independent meaning, as in a project that

is decomposed into activities, and activities are decomposed into their resources.

The database implementation is accomplished using the Microsoft Access 2000

environment (see the tables and relationships shown in figure 4.4). In essence,

these tables map the entities and their respective relationships. The data type of

the primary key in the entity tables is auto-number, which avoids the redefinition

of the key.

As shown in figure 4.5, we have 13 tables that cover the database thought

for this research. Some of these tables are dummy table, just to assure a many

to many relationship, or many to one relationship. Mainly the database is

modeled conceptually using 9 physical entities. The physical entities represent

the company, user, project, project details, materials details, erection drawings,

connection drawings, section details, and department details. These entities

record the internal information of the project being modeled such as names of

companies, projects, materials, sections…At the same time these entities are

related to each other with a logic combination to make them interacting with each

other. The input information at the beginning that will be stored in the database is

a mix of Microsoft Project columns input information, like activity name duration

of activity, and at the same time information provided by the manufacturer of

materials. In our case study it will be steel parts. It will include materials

specifications, quantities, and of course RFID tag numbers to identify the

materials. In addition to that, it includes information related to fabrication,

shipping and erection schedule.

74

Figure 4.5: Project Database Tables and their Relationships

4.4.2.1 Database Queries

Once the relationship and tables are established, next step is to perform

the required queries that will fulfill the need for this research. Some of the queries

constructed are fabrication schedule, shipping schedule, erection schedule,

section details, and project progress updates.

Figure 4.6 shows user interface of the database. Users just have to press

on one of the options available and the output will be displayed on the screen.

Figure 4.7 shows the output of the project update. At the beginning the

user has to enter the name of the activity, and then the remaining information will

appear.

Figure 4.8 shows erection drawings for certain section. It will include

details about the erection drawing pertaining to a certain section, in addition to

the connection details drawings. So the user on the construction site, having the

handheld computer in his hand, is able to access the information stored in the

database, and retrieve those information on a push of button.

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Figure 4.6 User Interface

Figure 4.7 Project Updates

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Figure 4.8 Erection drawings

Now that the framework of the real-time project tracking model was

presented, the next step is to develop an assessment system that will evaluator

to choose the right tools for the proposed model

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CHAPTER 5

TECHNOLOGY SELECTION AND ASSESSMENT MODEL

This chapter presents a multi-attribute utility model to help in choosing

between different alternatives of using new technologies on the construction

sites. The theory’s basic idea is that the selection issue can be broken down into

alternative attributes. Based upon the user’s tradeoffs among attributes,

important weights are quantified and single attribute utilities are measured.

Finally, single attribute utilities are combined to develop one single aggregate

utility index for each alternative.

5.1 Assessment Model

The assessment model is divided in two parts. The first part consists of

developing the utility function model that will help evaluator to choose between

available technologies for real time project progress tracking. This phase include

presenting the main objective and identifying the attribute that will help the

evaluators in their decisions, and the alternatives to be assessed. The second

part consists of analysis and identifying the best alternative that serves our need.

Figure 5.1 presents the Analytic Hierarchy process flow chat.

5.1.1 Defining the Problem

Improving the information sharing between participants can enhance the

performance of project management and control. The information sharing is

composed of two main aspects: information acquisition and information

communication. Information acquisition problems in a construction project result

from the fact that most of the data and information are gathered from the

construction site. The effectiveness of information and data acquisition influences

the flow of information between the office and the construction site.

78

Figure 5.1 Analytic Hierarchy Process

79

However, on site engineers usually use written documents, drawings,

contracts, specifications, and shop drawings for job sites. As a result a gap in

time and space between the job site and office causes the duplex, lack and

confusion of data and information. In other words, existing means of processing

information and collecting data are not only consuming and costly, but also

reduce the performance of project management in information acquisition.

Furthermore, construction contractors normally depend on interactions over the

telephone or fax machine to communicate with suppliers, subcontractors, and

designers. Consequently, transactions are often lost or misunderstood. Such

means of communicating information between sites and offices, and among all

participants, are ineffective and inconvenient.

As mentioned in chapter 3 a good way to improve communication on the

construction and between construction site and office is by using information

technologies that will provide a framework for a real time project progress

tracking.

Because the Utility function requires developing selection criteria for

evaluation technology, three main objectives were identified: (1) technical merit,

(2) economic merit, and (3) low risk merit. Systems utilities were calculated

based on the degree to which these objectives were achieved (Ghanem et al.

2007).

5.1.2 Explanation of Model Attributes

The attributes structure listed in figure 5.2 can serve as a basis for

evaluating the selected project progress tracking systems. This section explains

the model attributes. Technical criteria are represented by nine attributes such as

technical requirement skills. Users on the construction site try to resist new

technologies especially if it involves a lot of training and effort to learn how the

system functions.

Battery life is an important factor in determining how long batteries operate

before they need a recharge. Some of the equipments are supplied with

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rechargeable nickel cadmium cells. Others use disposable alkaline batteries.

Very few are powered by both types that include a backup source of power.

Wireless connection speed in order to update the host computer system

instantaneously as data reading occurs is a concern for people on the

construction site. Not all systems have this capability.

Rugged characteristic of the equipments used on the construction site

determine to what extent they can survive in harsh environment. These

equipment have passed durability tests up to military standards; they can

withstand falls, vibration, dust, and rain.

The screen size of both computers and PDA measured by inches is an

important attribute, because users have to check erection drawings and small

screen size tries to be an obstacle when tiny details need to be checked.

Some systems have the writing ability and others have the touching

screen ability. On the construction site while the user most of the time will be

standing and holding in one hand the equipment, probably it will affects its choice

regarding the writing system.

In addition to that the weight of the equipment is another concern when

the user will be holding it most of the time in his hand.

Another concern is the ability of the system to accommodate all required

software on the construction site. Mainly CAD and project management software

are a main concern for user on the construction site, in order to check the project

schedule and check the erection drawings when it is needed.

Accuracy of the system used especially when tags are being scanned on

the construction site is a concern too. Users tend to scan the tags from a

distance and interference with object or other tags has to be taken into

consideration.

Because technology cost is very important consideration, the initial

investment includes the equipment purchase cost, as well supporting cost for

software and accessories.

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Figure 5.2: Hierarchy of Influence as Applied in the Study

Operating cost should also be considered. It includes the cost of the tags

whether they are active or passive tags, the cost of system maintenance and the

updates that occur in the system.

82

Incorporating new technologies into a company system is believed to

improve the quality of processes. But at the same time lead to cut in labor or

some people see it as saving in labor.

Concerning the risk factor resulting from using new technology, all risk

factor are included under the low risk criteria. Each evaluator evaluates

technologies based on how certain or uncertain he is about the technology.

Sources of uncertainty are numerous. Some sources could be related to the

system itself, such as the security of the system and how it can prevent hacking

the system. Another issue is a reliability issue that is associated with new

technologies. Equipment and performance reliability fall into this category. Users

want to make sure that the equipments and system they are using are reliable

with minimum down time.

5.1.3 Defining Attribute Measuring Scales

When the model objectives and attributes were satisfactorily defined, the

quantification process started by defining system attributes measures. Table 5.1

lists the measuring scales for the defined attributes. The measures scale is

based on literature review, reviewing manufacturers and associations’ websites,

and exchanging email with experts (Elmisalami et. al.2006, Abduh and

Skibniewski 2002, Singletary 2006).

Table 5.1 Attributes Measures Attributes Measures

Technical Requirement Skills

Very Low/ Low/Moderate/High

Accuracy Very Low/ Low/Moderate/High Rugged Characteristic IP # # Screen dimension 2/3/4/5/6/7/8/9/10 (inches) Battery life 1/2/3/4/5/6/7/8/9/10 (Hours) Weight including Battery 0.5/1/2/3/4/5/6/7/8/9/10 (Lb) Writing Ability Typing/Touching Software Accommodation CAD/Project Management/Both Wireless Connection Speed

kbps- Mbps

Initial Investment % of Project Total Cost

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Table 5.1 Continued

Attributes Measures Operating Cost % of Project Total Cost

Saving in Labor Unsatisfactory/Moderate/Satisfactory /Very

Satisfactory

Quality Improvement Unsatisfactory/Moderate/Satisfactory /Very

Satisfactory Equipment Reliability Low/Moderate/High Performance Reliability Low/Moderate/High Investment Risk Low/Moderate/High Security Yes/No

As shown in table 5.1, some attributes are quantitative and others are

qualitative. Economic merit attributes, such as technology’s initial and operating

costs, are quantifiable. All system reliability attributes require subjective judgment

because the user has to specify his preference that systems meet or not meet

the attribute described.

5.2 Utility Function Survey

To obtain information about the preferences and the weight of the defined

attributes, a survey was sent to 200 people from different construction sites.

The first step was to determine the minimum number of respondents to

validate the survey. In a study conducted by Barlett, Kotrkik, and Higgins in 2001,

a table for determining minimum returned sample size for a given population size

was presented. According to them, an alpha level of 0.05 is acceptable for most

research. And for continuous data, a margin error of value 3% is acceptable.

Based on the tables presented by them, the minimum required returned sample

to validate the survey result should be 75 responds based on a population of

200. 60 people respondent to the survey, so we were short by 15. Salkind (1997)

recommended over sampling to reach the desired number. This method was

used and we ended up by receiving 77 filled surveys from people involved with

the construction industry in the form of both paper ballet and secured online

forms. The survey mainly contained two parts: the purpose of the first part was to

determine the set of priorities of the attributes in order to calculate the weight of

84

each attribute. The second part of the survey was to determine the utilities by

getting the evaluator preferences on the degree of liking for each attribute.

Appendix B contains the full form of the survey and the table developed by Barlet

et al. to determine the minimum size of survey filled.

Figure 5.3 illustrates the various job titles of the survey respondents. Most

of the responses are from engineers of companies with business areas in

building & civil construction. Other responses are scattered among all sectors

and job titles commonly found in the industry.

Figure 5.3 Job Title Survey Respondents

5.2.1 Measuring Weights

As mentioned before, the first part of the survey was used to determine

the preferences between the attributes. The pairwise comparison scale (table

3.1) presented by Saaty was used by the evaluator to represent the relative

importance of one element over another with respect to the criteria. The

responses to the pairwise comparisons at each level of the hierarchy were

placed into a comparison matrix. Only half of the matrices needed to be filled by

the evaluators because the other half is reciprocal. The numbers (on a scale 1 to

9) in the matrices corresponds to ratio scales.

85

Based on the hierarchy of influence established earlier, four pairwise

matrices needed to be developed. Figure 5.4 presents the four pairwise matrices

resulting from the hierarchy of influence. Each matrix represents the relative

importance of one attribute over another with respect to a specific criterion. The

numbers shown in these matrices are the final preferences established by the

evaluators from the survey.

For example in the matrix representing relative importance to fulfill real

time project progress tracking numbers (figure 5.4a), a value of 5 (first column

second row) means that economic criteria is 5 times more preferred to

technology criteria with respect to the model. At every level in the hierarchy, a

similar pairwise analysis is conducted for each criteria / subcriteria of that level.

Real time. Tech. Econ Risk

Tech 1 1/5 1/6

Econ. 5 1 1/3

Risk 6 3 1

(a) Relative Importance to Fulfill Real Time Project Progress Tracking

Econ. Init. Oper. Sav.Lab. Qual. Imp.

Init. 1 2 4 3

Oper. 1/2 1 2 3

Sav. Lab. 1/3 1/2 1 4

Qual. Imp. 1/3 1/5 1/4 1

(b) Relative Importance to Fulfill Economical Criteria

Risk Equ. Reli. Perf. Reli Inv. Risk Secur.

Equ. Reli. 1 1/2 1/7 1/6

Perf. Reli 2 1 1/2 1/4

Inv. Risk 7 2 1 1/3

Secur. 6 4 3 1

(c) Relative Importance to Fulfill Risk Criteria

Figure 5.4 Pairwise Comparisons

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Tech. Skills Rugged Scr. Dimen. Batt. Lif. Soft Accom. Wir. Speed Weight Writing Abil. Accuracy

Skills 1 1/3 1/4 1/5 1/4 1/4 3 1/5 1/2

Rugged 3 1 3 3 2 1/5 4 2 2

Scr. Dimen. 4 1/3 1 1/3 1/2 1/3 3 4 2

Batt. Lif. 5 1/3 3 1 2 3 5 2 2

Soft Accom. 4 1/2 2 1/2 1 1/3 5 2 3

Wirel. Speed 4 5 3 1/3 3 1 4 3 2

Weight 1/3 1/4 1/3 1/5 1/5 1/4 1 1/3 1/2

Writing Abil. 5 1/2 1/4 1/2 1/2 1/3 3 1 2

Accuracy 2 1/2 1/2 1/2 1/3 1/2 1 1/2 1

(d) Relative Importance to Fulfill Technological Criteria

Figure 5.4 Continued

The comparison matrices are evaluated to establish the priority vectors.

These vectors are weighted by multiplying them with the weight of the

corresponding criteria from the preceding level. Similar procedure is employed at

each level of the hierarchy.

5.2.2 Consistency Checks

A key step is the establishment of priorities through the use of the pairwise

comparison procedure as explained in the previous section. An important

consideration is the consistence of the judgments made by the evaluator. And as

a nature of human beings, perfect consistency is practically impossible to

achieve. So we need a method to measure the degree of consistency among the

pairwise judgments provided by the evaluator. If the degree is acceptable then

the decision process continues or else the values should be reconsidered and

possibly revise the pairwise judgments or the values should be discarded.

A measure of consistency used by the AHP that can be computed is

known as the consistency ratio (CR). This ratio is designed so that values of the

ratio exceeding 10% are indicative of inconsistent judgments, then either the

values of the matrix were rejected or additional steps were taken to modify

pairwise comparisons till acceptable consistency ratio was obtained.

Figure 5.5 presents the procedure that it has been followed in checking

each matrix. The feedback from each evaluator was checked independently

87

using equation 3.5 and 3.6, and in case CR was greater than 10% additional

steps were taken or in some cases the matrix was rejected. Out of the 77 people

who replied to the survey, 21 matrices were rejected cause of failure to the

consistency check.

The first matrix of each row represents the normalized pairwise. The

normalized matrix is calculated by adding the values in each column of the

pairwise comparison matrix, and then dividing each element in the pairwise

comparison matrix by its column total. The second matrix provides an estimate of

the relative priorities of the elements being compared. It is calculated by

computing the average of the elements in each row of the normalized matrix.

These values from each set of matrix were used to develop the weight of each

attribute.

Then consistency is calculated as follows:

Step 1: Normalize the comparison matrix by dividing the values of each column

over the sum of this column.

Step 2: Calculate the elements of the eigenvector matrix by averaging the

elements of each individual row of the normalized matrix.

Step 3: Calculate the transition matrix by multiplying the comparison matrix with

the calculated eigenvector.

Step 4: Calculate the matrix dominant eigenvalue noted (max using equation 3.4.

Step 5: Compute the Consistency Ration (CR) based on equation 3.6

Step 1 Step 2

Real time Tech.

Tech 0.08 0.05 0.11 0.08

Econ. 0.42 0.24 0.22 0.29

Risk 0.50 0.71 0.67 0.63

Normal Matrix Eigenvector Matrix

88

Step3 Step 4 Step 5

0.24

0.90 3.09 0.08

1.99

Transition Matrix Dominant Eigenvalue Consistency Ratio

(a) Consistency Check for the Main Goal

Step 1 Step 2

Econ. Init.Cost Oper.Cost Sav.Lab. Qual. Imp.

Init.Cost 0.46 0.54 0.55 0.27 0.46

Oper.Cost 0.23 0.27 0.28 0.27 0.26

Sav. Lab. 0.15 0.14 0.14 0.36 0.20

Qual. Imp. 0.15 0.05 0.03 0.09 0.08

Normal Matrix Eigenvector Matrix

Step3 Step 4 Step 5

2.02

1.13

0.81 4.22 0.08

0.34

Transition Matrix Dominant Eigenvalue Consistency Ratio

(b) Consistency Check for Economical Criteria Matrix

Step 1 Step 2

Risk Equ. Reli. Perf. Reli Inv. Risk Secur.

Equ. Reli. 0.06 0.07 0.03 0.10 0.06

Perf. Reli 0.13 0.13 0.11 0.14 0.13

Inv. Risk 0.44 0.27 0.22 0.19 0.28

Secur. 0.38 0.53 0.65 0.57 0.53

Normal Matrix Eigenvector Matrix

Step3 Step 4 Step 5

0.26

0.53

1.15 4.14 0.05

2.26

(c) Consistency Check for Risk Criteria Matrix

Figure 5.5 Consistency Checks

89

Step 1

Tech. Skills Rugged Scr. Dimen. Batt. Lif. Soft Accom. Wir. Speed Weight Writing Abil. Accuracy

Skills 0.04 0.04 0.02 0.03 0.03 0.04 0.10 0.01 0.03

Rugged 0.11 0.11 0.23 0.46 0.20 0.03 0.14 0.13 0.13

Scr. Dimen. 0.14 0.04 0.08 0.05 0.05 0.05 0.10 0.27 0.13

Batt. Lif. 0.18 0.04 0.23 0.15 0.20 0.48 0.17 0.13 0.13

Soft Accom. 0.14 0.06 0.15 0.08 0.10 0.05 0.17 0.13 0.20

Wirel. Speed 0.14 0.57 0.23 0.05 0.31 0.16 0.14 0.20 0.13

Weight 0.01 0.03 0.02 0.03 0.02 0.04 0.03 0.02 0.03

Writing Abil. 0.18 0.06 0.02 0.08 0.05 0.05 0.10 0.07 0.13

Accuracy 0.07 0.06 0.04 0.08 0.03 0.08 0.03 0.03 0.07

Normal Matrix

Step 2 Step 3 Step 4 Step 5

bil.

0.04 0.37

0.17 1.83

0.10 1.02

0.19 2.03

0.12 1.19 10.35 10.12

0.21 2.42

0.03 0.29

0.08 0.80

0.05 0.58

Eigenvector Matrix Transition Matrix Dominant Eigenvalue CR.

(d) Consistency Check for Technological Criteria Matrix

Figure 5.5 Continued

5.3 Procedure for Constructing Single Attribute Utility Functions

The evaluator from the survey provided their assessment of the UL and UH

value for each attribute. Table 5.2 and 5.3 show the average values of the

evaluator assessment for UL and UH respectively along with their standard

deviations

90

Table 5.2 Assessment of UL Attributes Assessment of UL Standard

deviation Technical Requirement Skills Low N/A Accuracy Low N/A Rugged Characteristic IP33 N/A Screen dimension 2 1.32 Battery life 4 1.26 Weight including Battery 6 2.94 Writing Ability Typing N/A Software Accommodation CAD N/A Wireless Connection Speed 56 Kb N/A Initial Investment 2% 0.78 Operating Cost 1% 0.36 Saving in Labor Moderate N/A Quality Improvement Moderate N/A Equipment Reliability Moderate N/A Performance Reliability Low N/A Investment Risk Low N/A Security No N/A

Table 5.3 Assessment of UH Attributes Assessment of UH Standard

deviation Technical Requirement Skills Moderate N/A Accuracy Moderate N/A Rugged Characteristic IP45 N/A Screen dimension 6 2.51 Battery life 8 3.43 Weight including Battery 2 .80 Writing Ability Touching N/A Software Accommodation Both N/A Wireless Connection Speed 2 Mb N/A Initial Investment 0.50% 0.21 Operating Cost 0.25% 0.94 Saving in Labor Satisfactory N/A Quality Improvement Satisfactory N/A Equipment Reliability High N/A Performance Reliability High N/A Investment Risk Moderate N/A Security Yes N/A

Though the risk attitude could differ among the different evaluators, it is

assumed that they have a neutral risk attitude. Thus a linear function could be

91

used to depict the utility between UL and UH (refer to figure 3.2). The utility

function would have the form:

ui(yi) = ciyi + di Equation 5.1

Where yi * [UL, UH]

Where ui(yi) = expected utility for measure I that is associated with value

yi; and ci, di = constants

Solving equation 5.1 requires two points on the linear function. Using the

average value of UL and UH from table 5.2 and 5.3, the constants ci and di can be

estimated.

The single attribute utility functions for the various attributes measures are

given in table 5.4.

5.3.1 Multiple Attribute Utility Function Development

The development of the multiple attribute utility function UT can be

constructed through integrating the single attribute utility functions and using the

preference structure calculated based on figure 5.4. The average weights vector

would be used as it depicts the most likely values for the sought preference

structure. For each alternative, the aggregate utility value is determined by

adding the product of the multiplication of each single-attribute utility with its

assigned weight.

UT = 0.0032U1(y1)+0.0136U2(y2)+0.008U3(y3)+0.0152U4(y4)+0.0096U5(y5)

+0.168U6(y6)+0.0024U7(y7)+0.0064U8(y8)+0.004U9(y9)+0.128U10(y10)

+0.075U11(y11)+0.058U12(y12)+0.024U13(y13)+0.04U14(y14)

+0.11U15(y15) +0.18U16 (y16) +0.33U17 (y17) Equation 5.2

Equation 5.2 presents the multiple attributes utility function to provide a

collective assessment of the assessed technologies for real time construction

project progress tracking.

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Table 5.4 Single Attribute Utility Functions

Attributes Designation

Technical Requirement Skills y1

Accuracy y2

Rugged Characteristic y3

Screen dimension y4

Battery life y5

Weight including Battery y6

Writing Ability y7

Software Accommodation y8

Wireless Connection Speed y9

Single attribute utility function ui(yi)

where 1=None, 2=CAD, 3= PM,4= both

u9(y9) ={0, y9 + 2

0.5y9 - 1, 2 <y9< 4

1, y9, 4

where 1=14 Kb, 2=56 Kb, 3= 256 Kb,

4= 2Mb, 5= 11Mb

u7(y7) ={0, y7 + 1

0.5 y7 - 0.5, 1 <y7< 3

1, y7 , 3

where 1=typing, 2=writing, 3= touching

u8(y8) ={0, y8 + 2

0.5y8 - 1, 2 <y8<4

1, y8 , 4

u6(y6) ={0, y6 , 6

- 0.25y6 + 1.5, 2 >y6 > 6

1, y6 + 2

u4(y4) ={0, y4 + 2

0.25y4 - 0.5, 2 <y4< 6

1, y4 , 6

u5(y5) ={0, y5 + 4

0.25y5 - 1, 4 <y5< 8

1, y5 , 8

where 1=very low, 2=low, 3= moderate,

4= high

u3(y3) ={0, y3 + 3

0.5y3 - 1.5, 3 <y3< 5

1, y3 , 5

0, y1 + 2

y1 - 2, 2 <y1< 3

1, y1 , 3u1(y1) ={

where 1=very low, 2=low, 3= moderate,

4= high

u2(y2) ={0, y2 + 2

y2 - 2, 2 <y2< 3

1, y2 , 3

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Table 5.4 Continued

Attributes Designation

Initial Investment y10

Operating Cost y11

Saving in Labor y12

Quality Improvement y13

Equipment Reliability y14

Performance Reliability y15

Investment Risk y16

Security y17

where 1=No, 2=Yes

Single attribute utility function ui(yi)

u16(y16) ={0, y16 + 2

y16 - 2, 2 <y16< 3

1, y16 , 3

where 1=very low, 2=low, 3= moderate,

4= high

u17(y17) ={0, y17 + 1

y17 - 1, 1 <y17< 2

1, y17 ,2

where 1=very low, 2=low, 3= moderate,

4= high

u15(y15) ={0, y15 + 2

0.5y15 - 1, 2 <y15< 4

1, y15 , 4

where 1=very low, 2=low, 3= moderate,

4= high

u13(y13) ={0, y13 + 3

y13 - 3, 3 <y13<4

1, y13 , 4

where 1=very unsatisfactory, 2=ununsatisfactory,

3= moderate, 4= satisfactory, 5= very

satisfactory

u14(y14) ={0, y14 + 3

y14 - 3, 3 <y14<4

1, y14 , 4

u12(y12) ={0, y12 + 3

y12 - 3, 3 <y12< 4

1, y12 , 4

where 1=very unsatisfactory, 2=ununsatisfactory,

3= moderate, 4= satisfactory, 5=

very satisfactory

u10(y10) ={0, y10 , 2

-0.66y10 + 1.32,0.5 >y10 > 2

1, y10 + 0.5

u11(y11) ={0, y11 , 1

-1.33 y11+ 1.33,.25 >y11 >1

1, y11 + 0.25

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The four alternatives that we are trying to investigate in this study are a

combination of mobile devices with wireless communication capabilities as

shown in table 5.5.

Table 5.5 Technology Alternatives

Alternative 1 Alternative 2 Alternative 3 Alternative 4 Rugged Tablet Computer & Radio Frequency Identification (RFID) reader & WLAN 802.11b

Rugged Tablet Computer & Radio Frequency Identification (RFID) reader & Wireless Subscription

Rugged Personal Digital Assistant (PDA)/ Radio Frequency Identification (RFID) reader & WLAN 802.11b

Rugged Personal Digital Assistant (PDA)/ Radio Frequency Identification (RFID) reader & Wireless Subscription

Table 5.6 illustrates the values of the attributes of the four alternatives

being considered in this study. Based on the single attribute utility functions given

in table 5.4, the corresponding utility values of the various alternatives are

calculated and listed in table 5.7.

Table 5.6 Alternatives Measures Attributes Alternative1 Alternative2 Alternative3 Alternative4

Tech. Requirement Skills

low low moderate moderate

Accuracy moderate moderate moderate moderate Rugged Characteristic

IP54 IP54 IP67 IP67

Screen dimension 8.4 8.4 2.5 2.5 Battery life 4 4 10 10 Weight including Battery

3.9 3.9 0.68 0.68

Writing Ability touching touching typing typing Software Accommodation

both both PM(FM) PM(FM)

Wireless Connection Speed

11 Mb 14 Kb 11 Mb 14 Kb

Initial Investment 1.17 1.11 0.86 0.79 Operating Cost 0.42 0.50 0.41 0.45 Saving in Labor satisfactory satisfactory satisfactory satisfactory Quality Improvement satisfactory satisfactory moderate moderate

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Table 5.6 Continued

Attributes Alternative1 Alternative2 Alternative3 Alternative4

Equipment Reliability high moderate high moderate Performance Reliability

high moderate high moderate

Investment Risk moderate moderate low low Security no yes No yes

Values of UT can vary between 0 and 1. The larger the UT value for an

alternative the more favorable it is to be used in the real time model. As shown in

table 5.7 for case study 1, the utility function of the four alternatives varied

between 0.59 and 0.93, which suggest that none of the four alternatives are

perfect enough to obtain aggregate utility close to 1. Although alternative 2 had

the highest utility of value 0.93 corresponding to the most favorable choice.

Table 5.7 Utility of Alternatives Case Study 1

UT(Alt1) UT(Alt2) UT(Alt3) UT(Alt4)

0.70 0.93 0.59 0.82

As shown in table 5.8 for case study 2, the utility function of the four

alternatives varied between 0.62 and 0.98, which suggest alternative 2 had the

highest utility of value 0.98 corresponding to the most favorable choice and the

closest to 1.

Table 5.8 Utility of Alternatives Case Study 2

UT(Alt1) UT(Alt2) UT(Alt3) UT(Alt4)

0.75 0.98 0.62 0.85

Both Case studies ranked Alternative 2 as the best alternative that fulfills

the need for real-time project progress tracking. Although in both case studies

alternative 2 had the highest life cycle cost with a value of $48,503 and $81,062

respectively for each case study. Even though Alternative 1 had the highest initial

cost, but the recurring cost for alternative 2 was the highest for both case study.

From this observation, a conclusion can be made that cost is not a major

attribute to establish which tools should be used in the real-time project progress

96

tracking model. Cost was embedded inside the assessment model as two

attributes: initial investment and operating cost. These two attributes are

represented as percentages of total cost of the project. So a sensitivity analysis

has to be done to determine the range of projects for which the cost will be a

major factor in taking decisions.

Another observation from the assessing model is noted. Evaluator gave

big importance for risk criteria, so it is good to know how this criteria influence our

choice. So another sensitivity analysis is conducted to see results change by

applying different risk scenarios.

Last but not least, an observation is made that both technical and

economical criteria have a complementary relationship. That mean the more the

requirements is needed, the more cost is associated with it. In this case the

attribute cost will get less value, but the technical merit will get greater utility

value and vice versa.

5.4 Sensitivity Analysis

The sensitivity analysis involved some additional calculation to examine

the effect of changing the model parameters on the final conclusion. The

sensitivity analysis in this research involves three different sensitivity analysis

tests. These tests are performed to check the assessment model response to

variation of preference weights in the pairwise comparison of criteria. The

following sections explain the effect of these factors in more detail.

5.4.1 Effect of Changing Cost

In the first test, the total cost is tested by changing the values of

alternative measures to three different values: 2%, 1%, and 0.5% corresponding

to a utility value: 0, 0.66, and 1 respectively as shown in figure 5.6. The other

attribute measures were kept to their original values.

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Cost Analysis

0

0.2

0.4

0.6

0.8

1

1.2

1 2 3 4

Alternatives

Uti

liti

es

2%

1%

0.50%

measure

Figure 5.6 Cost Analysis

The corresponding utility value for each cost variation is shown in table

5.9.

Table 5.9 Utility Variation Based on Cost

Alt.1 Alt.2 Alt.3 Alt. 42% 0.55 0.78 0.41 0.65

1% 0.75 0.98 0.62 0.85

0.50% 0.68 0.91 0.55 0.78measure 0.7 0.93 0.59 0.82

In all cases, alternative 2 had the highest utility value corresponding to the

favorite alternative to be used on the construction site. Another observation is

related to the order of alternative preferences. The same order was obtained

each time: (1) Alternative 2, (2) Alternative 4, (3) Alternative 1, and (4) Alternative

2. Plus it is hard to prove from these alternatives that both technological and

economical criteria are complimentary. The reason is these alternatives are very

close in their measures.

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5.4.2 Effect of Changing Risk Weight

Evaluator gave risk merit the highest weight with a value of 0.63. In our

assessment model, risk criteria included four attributes: equipment reliability,

performance reliability, investment risk, and security. To measure to which extent

risk affects the user preferences output, three different weights were used: 0.25,

0.50, and 0.75 maintaining the other weight the same. The values of the utilities

resulting are shown in table 5.10 and in figure 5.7.

Table 5.10 Utility Variation Based on Risk Weight Changes

Alt.1 Alt.2 Alt.3 Alt.4

0.25 0.489 0.58 0.49 0.59

0.5 0.607 0.8 0.53 0.73

0.63 0.7 0.93 0.59 0.82

0.7 0.7 0.97 0.57 0.85

Risk Analysis

0

0.2

0.4

0.6

0.8

1

1.2

1 2 3 4

Alternatives

Uti

liti

es

0.25

0.5

0.63

0.7

Figure 5.7 Risk Analysis

From the risk analysis table, it is safe to conclude that the values of

weights less than 0.63 led to a change in alternatives ranking. In this case,

Alternative 4 is the favored one. The order of preferences is: (1) Alternative 4, (2)

Alternative 2, (3) Alternative 1, and (4) Alternative 3.

99

Risk merit is an important criterion in our multi-attribute model, and it affects the

user preferences when changed.

100

CHAPTER 6

MODEL APPLICATION IN STEEL CONSTRUCTION CASE

STUDIES

Two construction steel sites were selected as an experimental case facility

to get the data for this research. Pre-engineered buildings require repetitive

operations and assembly of many structural elements. Current information and

communication technology can be incorporated in the operational process for

efficient assembly at the job site. The structural steel construction processes of

two projects were observed and modeled to represent an overview of the current

practices of existing steel operations, find out potential productivity problems and

sources of waste, and explore the potential possibilities for improving current

processes. The second part of this chapter is to model the improved steel

process and compare the productivity of both models by using simulation

software. This chapter includes also an assessment of the benefits of

implementing the proposed model.

6.1 Case Study

Two construction steel projects constitute our case studies. The

first project we had the opportunity to monitor the progress of the construction

from the beginning. The second project we got all required data from the project

manager.

6.1.1 Case Study 1: Turbocor Project

The first construction project is Turbocor project, a 65,000 sq. ft. home for

a Canadian-based air-conditioning compressor manufacturer located in

Innovation Park, Tallahassee, Florida. Construction began November 2005 and

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was completed in July 2006. Sperry & Associate Company, based in

Tallahassee, FL, was the design build firm responsible for the project. The total

project cost was approximately $3 million and was under the budgeted amount.

The project included the construction of one huge building divided into two

parts: the first part represented the A/C plant, and the second part represented

the offices. An aerial view of the construction site through differences phases of

the project is shown in Figure 6.1. For more details about the steel erection and

different phases of the project check Appendix B. The building is pre-engineered

steel building (PEB) with metal sheeting as wall and roof covers. The advantages

that PEB present are its fast completion, straight forward erection, and usually

the PEB fabricator is the one that perform the design. The PEB steel parts were

provided by American Eagle Company based in Columbus, Georgia. Compared

to conventional steel buildings, PEB offer numerous advantages especially when

it comes to low rise buildings. In addition to the lower initial cost and faster

delivery, owner will only have to deal with one party, Steel fabricator, for the

design and fabrication of buildings.

Figure 6.1 Different Construction Phases

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Figure 6.1 Continued

6.1.2 Case Study 2: Jefferson County High School Project

Jefferson County High School (JCHS) is located in Monticello, Florida off

U.S. Highway 19. Construction of the high school began in June 2003 and was

completed in July 2004. The Haskell Company, based out of Jacksonville, FL,

was the design-build firm responsible for the project. The total project cost was

approximately $12.6 million and was under the budgeted amount.

The project included the construction of nine total buildings. An aerial view

of the site near project completion is shown below in Figure 6.2. Eight of these

buildings are classrooms and offices. These buildings are also pre-engineered

steel structures with Metal-Stud- Crete (MSC) panel walls. MSC is a structural,

composite wall panel system combining regular hardrock concrete,

approximately two inches thick on the exterior, and standard light-gauge steel

framing on the inside. MSC's structural, composite shear connector bonds these

two common construction elements to create an engineered, load-bearing wall

designed to carry floor and roof loads, and to rapidly enclose the building.

The MSC panels were cast on site & then erected into place. A photo of

an MSC panel being fabricated is shown below in Figure 6.3. The other building

is the gymnasium/cafeteria, which is by far the largest structure. It was

constructed with a structural steel frame and concrete Tilt-Up panel walls. Tilt-Up

Construction uses panels of concrete, which are poured in horizontal molds at

the construction site and tilted up into place. The tilted panels are then locked

103

into place through different methods. Figure 6.4 shows a Tilt-Up panel being

erected.

Figure 6.2: Aerial View of JCHS Site Just Before Owner Move-In

Figure 6.3: MSC Panel Fabrication

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Figure 6.4: Tilt-Up Panel Wall Erection

6.2 Steel Construction Process Overview

In this section, the whole steel construction processes of fabrication,

shipping, and erection are described. Key materials brought in during each phase

of the steel construction process are briefly described.

6.2.1 Preplanning and Fabrication

At an early stage, Sperry Associates, general contractor and American

Building Company, steel supplier worked together to discuss project site

constraints. They also determined the steel erection sequence, which represents

the order in which a zone or section of the structural steel frame is delivered and

erected to improve the efficiency of loading, delivery, unloading, and erection.

Based on the requirement of the general contractor master schedule, and the

105

fabricator load schedule, the steel factory created the fabrication and shipping

schedule. Figure 6.5 shows the fabricator shop where PEB parts were being

fabricated and the piece mark labeled on the steel members. All steel parts are

numbered to correspond to a set of erection drawings which indicates the

location of each piece.

(a) Steel Shop (b) Part Marks

Figure 6.5 PEB Fabrication

6.2.2 Shipment and Unloading

Due to space limitation, the fabricated steel members were not

immediately shipped to the construction site, but they were stored in the storage

yard according to erection sequence. Upon delivery to the jobsite, receiving and

unloading of materials should take place as near as possible to the place of

erection. The lay-down area should be clean and leveled. A 3-ton forklift truck is

ideal for unloading, but a mobile crane is equally suitable. After unloading,

shakeout of the steel member took place. It involves organizing steels pieces on

site so that they can be efficiently erected as shown in figure 6.6.

(a) Unloading (b) Stakeout Part Marks Figure 6.6 Unloading Steel Members

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6.2.3 Steel Erection

The major components comprise of rigid frame, columns and rafter, eave

struts, purlins, girts, flange braces, end-wall columns and bracing systems which

may be cables, rods angles or portals.

All materials for the first bay erection were prepared. The rafter sections

required were identified by part number, and then assembled as near as possible

to their lifting positions. Then the first four columns were erected at the braced

bay, meanwhile the part number and orientation, and position over anchor bolts

were verified. Next step was to position the crane for lifting the assembled rafter

sections. Figure 6.7 shows the erection process as the columns are lowered

carefully to be fixed on the anchor bolts. The last picture shows worker fixing

purlins on the rafters.

(a) Column Lowered (b) Fixing Column (c) Fixing Purlins on Rafters

Figure 6.7 Erection

6.3 Model the Existing Steel Construction Processes

Based on the field observation in the previous section, a diagram of

materials and information flow was formulated to represent the flows of

information and materials throughout the fabrication, shipping, and erection

phases. Experience and interviews with key players was used to model the

existing processes. This diagram provides us with a guideline of what information

107

the steel crew needs to perform a specific task, how data are shared, and where

to get those data from. This helps us to diagnose existing PEB steel construction

processes to find out alternative processes. Figure 6.8 presents the materials

and information flow of the PEB steel construction processes.

Figure 6.8 Materials and Information Flow

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As seen in the diagram, information and materials are passed from one

party to another via conventional approach. Key data sources within the defined

system are: fabricator, worker, foreman, and site manager. The next two sections

will define the productivity of the current practices and need for improvement.

6.4 Productivity Measurement

Spending time on the construction and observing tasks and movements of

the steel crew allowed us to collect productivity ratings data for PEB steel

operation. It is not possible to observe and analyze all of the tasks. Therefore,

sample measurement was taken for different processes and it was then

incorporated into a simulation model to measure work productivity.

Oglesby proposed three classifications for productivity ratings. The

classifications are: effective, contributory, and ineffective (Oglesby et al., 1989).

The percentages of crew time in all categories of the shakeout, unloading and

erection operations are summarized in table 6.1. The percentage rate is

calculated by dividing the observed number in each category by the total

observation.

It is noted that only 32% of total crew time was spent on the effective work

for the shakeout, unloading and erection operations while the contributory work

took 33% of crew time. The ineffective work accounts for 35% of crew time on

the average. Average time spent walking empty-handed, idle, non-work related

communication, searching for materials, and break time are respectively 5%,

10%, 9%, 5%, and 4%. These kinds of activities must be the areas to be

addressed for productivity improvement.

On the other hand, continuous time study involves the measurement of time

required to address the specific job under present conditions. Among all process,

we were interested into 4 of them: shipping, unloading, shakeout, and erection

operation. Those constitute one cycle in our study. It was proposed that

continuous time study be made of an average of three cycles for unloading,

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shakeout and erection. The next section presents the implementation of our

study into a simulation model to study the cycle productivity.

Table 6.1 Productivity Ratings Percent of Total Number (Shakeout, Unloading & Erection)

Categories Items

Foreman Erector1 Erector2 Worker1 Worker2 Average

Effective Work

10% 36% 29% 30% 33% 32%

Communication 33% 14% 10% 15% 15% 17%

Searching for materials and tools

2% 20% 15% 9% 9% 11%

Read document

20% 0% 0% 0% 0% 4%

Contributory work

Subtotal 55% 34% 25% 24% 24% 33%

Walking empty-handed

6% 52% 7% 3% 3% 5%

Idle 4% 7% 10% 15% 17% 10%

Correcting error

0% 0% 0% 0% 0% 0%

Non work related communication

20% 4% 5% 9% 3% 9%

Searching for materials

2% 8% 6% 6% 8% 5%

Break time 2% 6% 1% 3% 3% 4%

Non identifiable 1% 0% 25% 10% 9% 9%

Ineffective work

Subtotal 35% 30% 17% 46% 43% 35%

Total 100% 100% 100% 100% 100% 100%

6.4.1 PEB Simulation Model

Micro Cyclone is used in this study in order to study the construction steel

processes. The elements of Micro Cyclone, originally developed by Halpin, are

used to model and simulate PEB steel operations.

The model formulated took into consideration the delivery and the

availability of the steel parts on the construction site. In addition to that, in case

110

there was a problem with erection or with the steel parts, there is a

communication back and forth between the construction site and the steel

fabricator. Based on a lot of trial and error and trying different simulation model,

the author decided to separate both the shipping process from the erection

simulation process. The reason behind it is shipping process takes more time

then erection and when placing both processes into one simulation model the

results looked inaccurate.

Figure 6.9 and 6.10 presents PEB steel simulation model for both shipping

and erection. The shipping model is formed of 10 entities covering one cycle of

the process. The cycle starts from loading the materials at the fabricator shop till

offloading material on construction site. The erection model is formed of 30

entities covering one cycle of the process. The cycle starts from steel parts

available on the constructions site till erection of one bay of the steel structure.

Once the graphical model was established the next step is to transform it

into an input language that Micro Cyclone understands. Appendix D includes the

input files for both simulation files. Durations and Resources were also

incorporated in the input file. The duration units used in the input file is hour.

Some entities that represent inefficiency in the processes were included in the

model. Once the user gets familiar with Cyclone program, transition from

graphical input to computer language the simulation software understand

become easy step. Web Cyclone is case sensitive and all typing should be done

in upper case letters.

As you notice in the model, some resources were idle when others were in

use. Next section discusses those entities, especially that they represent

opportunity for improvement our processes and increase efficiency and minimize

waste. The simulation output will be discussed, once the To Be information flow

diagram is established and its simulation model is performed.

111

Figure 6.9 Shipping Simulation Model

112

Figure 6.10 Erection Simulation Model

6.4.2 Process Inefficiency

PEB steel parts are required to be installed in a specific order due to

structural safety requirements and to the logical sequence of erection. However,

shipping, transportation, unloading and on-site storage doesn’t take into account

the erection order of assembly. As a result, a considerable time was consumed

113

locating, sorting, and identifying steel components. Instead of setting the steel

directly off the delivery trucks, all the steel was off loaded and shakeout was

done as the steel was delivered. This practice resulted in double handling of

materials in the erection operations.

Once fabricated, the fabricator labeled each steel member with a unique

piece mark and sequence number to identify it directly on the erection drawings

and its proper place. However, to make it easy to find materials for erection, the

workers marked each piece one more time with white chalk based on the

erection hand map they made. This process leads of course to considerable

unproductive duplication.

Another concern is raised when workers try to locate the exact material to

be erected. Foreman determines the exact order in which each steel member

has to be erected. Workers identify components with paper-based information.

As a result, a significant portion of time is spent in the lay-down areas searching

by hand to identify components.

During our interview with the people on the construction site, it was found

that material and information flow can be lost, disconnected and distorted while

flowing from information sources to end user. Good examples were given to the

author when he was on the construction site. Workers didn’t know when next

shipping date is scheduled. Connectors had no full idea of where each steel

element was positioned. Foreman had no idea of the status of a shop drawing

approval after implementing some changes and which sequence of steel

elements was fabricated and stored at the factory and ready to be shipped.

It was also noticed that critical information from the field to the office had a

delay and lacked real time touch. According to the productivity ratings data

mentioned in table 6.1, foreman spent most of his time communicating with

workers, 33% of his time on work related communication and 20% for non-work

related communication. These percentages are higher than the average values,

17 % and 9% respectively.

Another two communication problems identified with the current process

are with the approval drawings and request for information. Actually usual delays

114

associated with the steel supply process are encountered during approval stage

of shop drawings. Many weeks are wasted due to movement of hard copy

drawings from one party to another.

The other major delay in case problem aroused on the jobsite and can’t be

resolved at the field office, so the site engineer had to submit a request for

information (RFI) to the technical engineering department. RFIs were sent via fax

with a sketch and a reference in the drawings and in case photos were attached

they had to be mailed by federal express. This would delay RFI turnaround times.

6.5 Steel Construction Process Updated

A significant number of problems were identified in the previous section

resulting from inaccurate data transfers as well from delays and interruption in

information flow, thus leading to a wasteful operation and inefficiencies in some

processes. So a new approach needed to be developed to not only ensure

control of information in a timely manner, but also increase level of

communication between multiple processes units for structural steel construction.

The main purpose of this section is to present the improved processes on

the construction site after implementing the proposed model, and at the same

time to present the benefit of implementation by comparing the outputs of the

simulation models.

6.5.1 Development of a data flow diagram

In order to identify the benefits resulting from implementing the proposed

model for structural steel construction processes, “To Be” data flows diagrams

were determined based on the field observation. In the data flow diagram as

shown in figure 6.11, key issues that were addressed include real time piece

tracking, retrieval of information related to the steel parts, like its location on

erection drawings, position and its orientation, and updating the construction

schedule.

115

Figure 6.11 Proposed Materials and Information Flow

116

When the steel component’s identity can be read directly through a

portable RFID reader, the erection sequence and position information of each

piece in their final location are automatically extracted from the common

database through wireless networks in real time. This situation makes

information stored in the database accessed at any time by people on the

construction site, and updates make construction activities from the jobsite

available to all process units who need the information in real time.

6.5.2 Proposed Process

Construction materials may account for 50-60% of the total cost of a

construction project of the elements that comprise the constructed facility. In

industrial and heavy construction, mostly prefabricated objects, such as structural

steel, pre engineered building and precast concrete elements, are used and

installed on site. If the right material could be easily and precisely tracked, found,

and distributed to the right location at the right time, tremendous benefits would

ensue. Reducing unsuccessful searches for materials would reduce wasted

supervisory time, crew idle time, and disruptions to short interval planning, and

hence help to increase labor productivity, reduce materials stock piles, and

reduce materials management manpower (Bell & Stuckhart 1986).

The case studies presented in this research are mainly construction sites

with a traditional construction materials management processes involving

multiple manual checking, recording and tracking processes as unique tagged

materials are transferred between parties along a supply chain approach. In the

example of pre-engineered buildings, as stated before we were interested in

three main processes: fabrication, shipping and erection on the construction site.

First, fabricator fabricates the steel parts and then they are painted at

paint shop. Once painting is finished, materials are tagged with RFID tags and

stored in the fabricator store yard till it is time to ship them to the project site. The

tag includes holders with two slots that accept a tie-wrap plastic fastener to

attach the tags to the steel parts. Tags can be attached to the steel parts using

plastic ties and double sided tapes. Finally, the contractor on the job site receives

117

the pieces stores them before the installation. There may be as many as 2,000

fabricated steel parts in an average size of buildings.

Radio Frequency Extenders (RFEs) can used as transceivers (readers)

that provide a communication link between the PC software and the tags as

shown in figure 6.12. RFEs are connected together and to the PC via Ethernet

cables. Data is written to any tag by connecting the laptop to the portal and a

single RFE.

Figure 6.12 Copying information to the RFID tags (Fiatech 2007)

The truck loaded with steel materials arrives at the project job site and is

sent to one of the designated laydown areas. Workers are provided with

handheld computer/ RFID reader. The reader used has a form like a standard PC

card and can be incorporated into the existing handheld computer using a PC

card expansion pack. Omni antenna and software are also installed in the

handheld computer. So worker at the laydown area identify the pieces using

RFID readers, and coordinate the unloading and storage of the steel parts. Any

discrepancy between the packing list and the steel parts unloaded from the truck

is sent back to the fabricator for resolution, or in case there are discrepancies

between the bill of materials and the unloaded materials, it will be directly

118

captured and fabricator will be contacted. Savings are captured when the

simulation model for the improved process is performed, especially with the

improvement in productivity.

6.5.3 Simulation Model

Figure 6.13 and 6.14 presents PEB steel simulation model for both to be

shipping and to be erection. The shipping model is formed of 11 entities covering

one cycle of the process. The cycle starts from loading the materials at the

fabricator shop till offloading material on construction site and it included the

tagging of the steel parts with RFID tags. The erection model is formed of 30

entities covering once cycle of the process. The cycle starts from steel parts

available on the constructions site till erection of one bay of the steel structure.

This process is improved by eliminating some of the wasted time to locate the

right material and to go back to the site office to get erection drawings and get

details of connections.

Once the graphical model was established the next step is to transform it

into an input language that Micro Cyclone understands. Appendix D includes the

input files for both simulation files. Durations and Resources were also

incorporated in the input file. In this simulation model, after implementing the

proposed model and improving the different processes by using wireless

technologies, the duration assigned for each activity changed accordingly, time

wasted occurred in the previous model, were eliminated, some activities were

deleted which make the cycle faster, and most importantly productivity increased

as will be shown in the output of both simulation model. The output of the

simulation models are attached in Appendix D. These outputs contain different

information about process productivity and resources status through the different

phase of the simulation.

119

Figure 6.13 Proposed Shipping Simulation Model

120

Figure 6.14 Proposed Erection Simulation Model

6.6 Simulation Outputs

The main output of simulation is the productivity result, which shows the

number of cycles per unit duration. This productivity data is what can be used to

evaluate the performance of a process design at a glance. A site engineer can

also use the sensitivity analysis function to try to improve the productivity of a

process by changing the resources. Based on Web CYCLONE, the construction

121

simulation result of a repetitive cycle in both projects was presented as the

productivity. For computing productivity of both shipping and erection process,

‘Hours’ was used as the time unit as shown in table 6.2

The cycle number in Table 6.2 represents the number of time both

systems cycle. For instance, one cycle of shipping steel materials (Refer to

Figure 6.9) includes Queue node (1: Steel batch) to Queue (10). In case of

erection process (Refer to Figure 6.10), Queue node (4: Steel Available) to

accumulator (30) is included in the one cycle of the system. It is usually defined

by user. Therefore, the productivity of shipping can be calculated through dividing

‘Cycle number’ by ‘Total simulation time (i.e., 30/107.3 = 0.279) and 300 / 2155.9

= 0.139 for erection). The same is done for the To Be processes.

Table 6.2 Simulated Productivity Results Total

Simulation Time (unit)

Cycle No.

Productivity (per time unit)

Production/Cycle Productivity

Shipping 107.3 30 0.279 1 truck 0.279 truck per hour

Proposed Shipping

67.1 30 0.447 1 truck 0.447 truck per hour

Erection 2155.9 300 0.139 1 bay 0.139 bay per hour

Proposed Erection

1699.3 300 0.176 1 bay 0.176 bay per hour

Based on the simulated productivity table, it takes 3.58 hours in order for

one truck to reach the construction site using the conventional process. On the

other hand it will take 2.24 hours in order for one truck to reach the construction

site. At the same time it takes 7.19 hours to erect one pre engineering steel bay.

But using the proposed process it will take 5.68 hours to erect one bay.

As summary, there will be saving in money at least one hour in the

shipping process and 1.5 hours in the erection process. Next section will quantify

those benefits and turn it into dollars.

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6.7 Proposed Model Benefits

The objective of this section is to analyze the values of the integrated

wireless technologies model functions. Because the multifaceted benefits of the

various applications, different scientific methods will be used to measure the

value that the technology integrated model will incorporate into the construction

process. The first step is to establish the cost of the technology that was used in

this research and this can be achieved by conducting a life cycle cost analysis

(LCC).

The study period for this LCC is taken for one year, because benefits are

calculated for one-year period. Discount rates and inflation rates were estimated

as average figures. Some numbers were based on the previous research done

by Mr. Singletary (2006). Initial cost inputs and calculations are illustrated in table

6.3 and table 6.4. All the direct initial costs involved with purchasing the

necessary equipment were determined during the equipment selection and

alternative identification steps. Estimates for training and maintenance costs

were determined from contacting products representatives. Salaries of people

involved in the construction project were determined by consulting U.S.

Department of Labor. The cost of computer hardware was obtained by contacting

Xplore Technologies representative.

A study conducted by Venture Development Corporation after checking

approximately 260 different companies using computing solutions, showed that

the increased cost associated with service, support, and downtime of commercial

grade computers outweighed the increased initial cost of purchasing rugged

computers. The average figures for downtime per year associated with rugged

computers was used in the LCC analysis to calculate downtime due to device

failure.

All costs have been discounted back to the beginning of the first month

using the adjusted monthly discount rate. It has been assumed that planning &

feasibility costs were incurred at the same time as the equipment purchases and

123

other initial costs. The total present worth of life cycle costs for each alternative is

shown.

Table 6.3 LCC Input Data

LIFE CYCLE COST INPUT DATA

Category Name Value Unit Notes

Computer Hardware

Rugged Tablet

Base 802.11b comes standard

Sunlight-Readable Screen

512 Mb

2nd Battery Extended Life up to 5 Hrs

Camera

Walking Bag

Integrated EDGE-GPRS

$4,476 $/EA

1 to 9 Units -$448 $/EA

Rugged PDA

Base $1,595 $/EA

Vehicle Charging Cable $44 $/EA 10 Hr. battery operation

Camera Bundle $315 $/EA

802.11b CF Card Kit $265 $/EA

GPRS/GSM CF Card $441 $/EA

1 to 14 Units -$100 $/EA

Maintenance $500 $/Yr

Training - - Combined w/ Software

Downtime Due to Device Failure 30

Hrs/Yr/ EA

Smart Chips Hardware

RFID Reader $1,500 (2 readers needed)

Antenna $300 $/EA

RFID Tags $0.10 $/EA

Software $100 $/EA

Training Free

(System is straight forward)

124

Table 6.3 Continued Computer Software

Microsoft Office $550

Field Manager (FMngr) $300 $/EA

Pocket CAD $199 $/EA

Maintenance & Upgrades 20%

value $/EA First Year Free

Training

Manuals $150 $/EA

Instructor Comes to Location $2,000 $/Day Plus Traveling Expenses

Employees Travel to Instructor

1 to 25 $1,200 $/Day Plus Traveling Expenses

25 to 49 $1,100 $/Day Plus Traveling Expenses

50 + $1,000 $/Day

Plus Traveling Expenses

Wireless Communications

WLAN 802.11b

Access Point (AP) $527 $/EA

Power Cables $39 $/EA

Protective Enclosure $156 $/EA

Omni-Directional Antenna $106 $/EA Increase Range by 60%

Maintenance $168 $/AP 3 Yr. Service Agreement

Downtime Due to Network Failure 30 Hrs/Yr

For Entire Network

Training - - Included w/ IT Support

Wireless Subscription

Tablet $80 $/Month

PDA $50 $/Month

No Training or Maintenance

Downtime from Network Failure 30 Hrs/Yr

Estimate Based on TCO Model

125

Table 6.4 LCC Calculations

CALCULATIONS

Category Name Value Formula

Planning & Feasibility

Planning & Feasibility $1,800 5Days*8Hrs.*(APM-

wage+ IT-wage)

Computer Hardware

Rugged Tablet/Smart Chips - Wireless Subscription $17,148

[Tablet + Smart Chips+ Upgrades + Accessories + Quantity Discount] * TNU

Rugged Tablet/Smart Chips - WLAN $17,280

[Tablet + Smart Chips+ Upgrades + Accessories + Quantity Discount] * TNU

Rugged PDA/Smart Chips - Wireless Subscription $12,590

[PDA+ Smart Chips + Accessories (GPRS Card) + Quantity Discount]* TNU

Rugged PDA/Smart Chips - WLAN $12,722

[PDA+ Smart Chips + Accessories (802.11b

card kit) + Quantity Discount] * TNU

Computer Software

Tablet Software $3,597 (Microsoft Project+ CAD) *

TNU

PDA Software $1,947 (FMngr +CAD )* TNU Wireless Communications

WLAN $2,052 (AP + Cables + Enclosure

+ Antenna) * 2 APs

Wireless Subscription

Activation Fee $105 $35 * TNU

Tablet $240 $80/Mo * TNU

PDA $150 $50/Mo * TNU

Training

Hardware & Software $2,250

$2000/Day * 1 Day + Instructor Traveling

Expenses

Staff Time Spent Training $1,076

8Hrs (SI-wage + Site Engineer-wage+ PM-

wage) Maintenance & Upgrades

Hardware Maintenance $1,500 $500/Yr. * TNU

Software Maint.& Upgrades

Tablet $1049/Yr 0.2 * Software Value

PDA $699/Yr 0.2 * Software Value

Wireless Communications Maintenance $168

Note: 3 year Service Agreement, Initial Direct

Cost

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Table 6.4 LCC Continued Wireless Consultant

Network Implementation & Upkeep $152 / 3Mo (IT wage * 8Hrs.)

On-Going Training

On-Going Training $208 / 6Mo APM-wage * 8Hrs

Staff Time Spent Training $240 / 6Mo FM-wage * 8Hrs

Downtime Due to Device Failure

Computer Failure $4,366

30Hrs/Yr *(SI-wage + Site Engineer-wage+ PM-

wage)

Network Failure $4,366

30Hrs/Yr *(SI-wage + Site Engineer-wage+ PM-

wage) Interest Rate Calculations

Effective Monthly Inflation Rate = fM 0.19%

fM = (1+fY)^(1/M)-1 (M = # of Periods per Year

= 12)

Monthly Discount Rate = rM 1.00% rM = r/M

Constant Effective Monthly Discount Rate = iM 0.81% iM = (rM - fM)/(1+fM)

A summary of the LCC analysis is shown in table 6.5 and 6.6 to cover

both case studies. All costs have been discounted back to the beginning of the

first month using adjusted monthly discount rate. Planning and feasibility costs

are assumed to be incurred at the same time as equipment purchases. The total

present worth of life cycle cost for each alternative is shown. Even though only

one alternative will be discussed later on when cost benefit analysis will be done,

but the LCC for all other alternatives were done, because it was used as an

attribute to determine the best alternative that satisfy the projects technological,

economical and risk criteria.

The variation in the total LCC for the four alternatives was around $10,000

for case study 1. The cheapest alternative is rugged PDA/smart chips with

wireless subscription. The most expensive alternative is rugged tablet/smart

chips with WLAN connection. Each investment situation is unique and requires

diversified investment choices. Therefore, in today’s complex and dynamic

127

construction environments, it is risky to rely on one method. It is necessary to use

multiple methods and compare their output against each other. Next step is to

conduct a cost benefit analysis and break-even analysis.

Table 6.5 LCC Summary (Case Study 1)

Financial Analysis Variables

Name Value Units Notes

Nominal Discount Rate 12.00% % Opportunity Cost of Capital (r)

Constant Inflation Rate 2.25% % Effective Annual Rate (f)

Adjusted Monthly Discount Rate 0.81% % iM = (rM - fM)/(1+fM)

System Life Cycle 12 Months Duration of Project

LCC SUMMARY

Tablet-WLAN

Tablet-Wireless

Subscription PDA-WLAN

PDA-Wireless

Subscription Month

Incurred

Initial Costs

Planning & Feasibility $1,800 $1,800 $1,800 $1,800 0

Hardware $17,148 $17,280 $12,590 $12,722 0

Software $10,791 $10,791 $5,841 $5,841 0

Wireless Communications $2,052 $105 $2,052 $105 0

Training $3,326 $3,326 $3,326 $3,326 0

Wireless Consultant $152 $152 $152 $152 0

Total Initial Costs $35,269 $33,454 $25,761 $23,946

Recurring Costs

Hardware Maintenance $125 $125 $125 $125 1-12

Software Maintenance $1,049 $1,049 $699 $699 12

Wireless Consultant - Network Maintenance $152 - $152 - 3,6,9,12

Wireless Subscription - $240 - $150 1-12

On-Going Training $448 $448 $448 $448 6

Downtime Due to Device Failure $727 $727 $727 $727 1-12

PW Recurring Costs $12,777 $15,049 $12,427 $13,619

Total PW LCC $48,046 $48,503 $38,188 $37,565

The variation in the total LCC for the four alternatives was around $25,000

for case study 2. The cheapest alternative is rugged PDA/smart chips with

WLAN. The most expensive alternative is rugged tablet/smart chips with Wireless

subscription. Each investment situation is unique and requires diversified

investment choices. Therefore, in today’s complex and dynamic construction

128

environments, it is risky to rely on one method. It is necessary to use multiple

methods and compare their output against each other. Next step is to conduct a

cost benefit analysis and break-even analysis.

As we can notice, the cost of the model for case study 2 is more

expensive than case study 1, and that can be explained by the fact that case

study 2 jobsite is much bigger than case study 1, and its location is farther from

steel manufacturer.

Table 6.6 LCC Summary (Case Study 2) Financial Analysis Variables

Name Value Units Notes

Nominal Discount Rate 12.00% % Opportunity Cost of Capital (r)

Constant Inflation Rate 2.25% % Effective Annual Rate (f)

Adjusted Monthly Discount Rate 0.81% % iM = (rM - fM)/(1+fM)

System Life Cycle 12 Months Duration of Project

LCC SUMMARY

Tablet-WLAN

Tablet-Wireless

Subscription PDA-WLAN

PDA-Wireless

Subscription Month

Incurred

Initial Costs

Planning & Feasibility $1,800 $1,800 $1,800 $1,800 0

Hardware $35,499 $35,499 $22,133 $23,365 0

Software $10,791 $10,791 $5,841 $5,841 0

Wireless Communications $3,480 $245 $3,480 $245 0

Training $3,326 $3,326 $3,326 $3,326 0

Wireless Consultant $152 $152 $152 $152 0

Total Initial Costs $55,048 $51,813 $36,732 $34,729

Recurring Costs

Hardware Maintenance $292 $292 $292 $292 1-12

Software Maintenance $3,909 $3,909 $2,049 $2,049 12

Wireless Consultant - Network Maintenance $152 - $152 - 3,6,9,12

Wireless Subscription - $560 - $350 1-12

On-Going Training $448 $448 $448 $448 6

Downtime Due to Device Failure $1,205 $1,205 $1,205 $1,205 1-12

PW Recurring Costs $22,939 $29,249 $21,251 $24,980

Total PW LCC $77,987 $81,062 $57,983 $59,709

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6.7.1 Function A: Site Inspection Savings

This function addresses the need of three common types of inspection: 1)

structural, 2) material, and 3) safety. A structural inspector compares design

documents with the actual installation. In several locations during our site visit,

the structural inspector, Mr. Ramon Piera (case study 1), was faced with an

unclear design document, requiring him to get clarification from the designer

(situated in main office in Alabama). A material inspector verifies that a material

meets the requirements of the applicable specification. A safety inspector

identifies potentially hazardous situations and supervises compliance with safety

regulations. The suitable implementation of function A returns savings in travel

cost and time from jobsite to the site inspector’s remote office as well as

inspection time. Baseline assumptions for case study 1 are formulated to

calculate annual benefits.

• 30 % of the total inspections can be remotely supported by this function

• At least 30 minutes of inspection time per inspection

• The frequency of site inspection: two times per week

• Driving distance:150 miles

• Average driving cost per mile: $0.36

• Average cost per man-hour of the site inspector: $70 (U.S. Department of

Labor)

Based on the assumptions above, the annual benefits of this function are

projected in table 6.7.

Table 6.7 Benefits Calculation of Function A Driving Cost 150miles*($0.36/mile)*(4weeks/month)

*(12months/year)*30% *(2 inspection/week)

$1,555

Travel Time Cost

150min*(1hour/60min)*($70/hour) *(4weeks/month)*(12months/year) *30%*(2 inspection/week)

$5,040

Inspection Time Cost

30min*(1hour/60min)*($70/hour) *(4weeks/month)*(12months/year) *30%*(2 inspection/week)

$1,008

Total Cost per Inspector $7,603

130

Baseline assumptions for case study 2 are formulated to calculate annual

benefits.

• 30 % of the total inspections can be remotely supported by this function

• At least 30 minutes of inspection time per inspection

• The frequency of site inspection: two times per week

• Driving distance:200 miles

• Average driving cost per mile: $0.36

• Average cost per man-hour of the site inspector: $70 (U.S. Department of

Labor)

Based on the assumptions above, the annual benefits of this function are

projected in table 6.8.

Table 6.8 Benefits Calculation of Function A

Driving Cost 200miles*($0.36/mile)*(4weeks/month) *(12months/year)*30% *(2 inspection/week)

$2,073

Travel Time Cost

200min*(1hour/60min)*($70/hour) *(4weeks/month)*(12months/year) *30%*(2 inspection/week)

$6,720

Inspection Time Cost

30min*(1hour/60min)*($70/hour) *(4weeks/month)*(12months/year) *30%*(2 inspection/week)

$1,008

Total Cost per Inspector $9,801

The benefits summarized above include the direct benefits to the system

related to inspection. In addition to the direct benefit, there are also several

possible indirect benefits (e.g., fast turnaround time to complete inspections)

involved in system implementation. However, it is extremely hard to quantify

indirect benefits in term of dollars.

6.7.2 Function B: Problem Solving Savings

As mentioned in previous chapters, inaccurate drawings and structural

pieces result in costly problems because they commonly require significant time

and effort to find solution (e.g. RFI process). With function B, field personnel will

131

have direct access to any information from off site experts who have more

experience, or able to solve design problems or other errors, using technology

integrated communication tools. An obvious benefit of function B is a reduction in

travel cost and RFI processing time. To determine number of RFIs cases for our

case project, the RFIs log was examined. The RFIs log maintained 256 RFIs

during 4 months between many different companies as shown in Appendix C.

Most of the RFIs were generated between Sperry associates and the PEB

manufacturer company American Buildings Company. Based on this information,

the following baseline assumptions are formulated.

• 1 hour of RFI processing time can be saved by the use of function B

• The frequency of an on site visit is one visit every 5 RFIs

• 100% of total site visits can be remotely supported by function B

• Average cost per man hour of an engineer: $96 (U.S. Department of

Labor)

Based on assumptions above, the benefits of function B (Case study 1)

are calculated in table 6.9.

Table 6.9 Benefits Calculation of Function B

Driving Cost

150miles*($0.36/mile)*(256RFI/4months) *(12months/year)*(1visit/5RFIs)

$8,294

Travel Time Cost

150min*(1hour/60min)*($96/hour) *(256RFIs/4months)*(12months/year) *(1visit/5RFIs)

$36,864

RFI Processing Time

1hour*($96/hour)*(256RFIs/4months) *(12months/year)*(1visit/5RFIs)

$14,746

Total Cost per Engineer $59,904

Case study 2 didn’t provide us with the required information, so we had to

use assumption made in case study 1 as shown in table 6.10.

132

Table 6.10 Benefits Calculation of Function B Driving Cost

200miles*($0.36/mile)*(256RFI/4months) *(12months/year)*(1visit/5RFIs)

$11,058

Travel Time Cost

200min*(1hour/60min)*($96/hour) *(256RFIs/4months)*(12months/year) *(1visit/5RFIs)

$49,152

RFI Processing Time

1hour*($96/hour)*(256RFIs/4months) *(12months/year)*(1visit/5RFIs)

$14,746

Total Cost per Engineer $74,956

Indirect benefits (e.g., reduction in construction downtimes or RFIs

turnaround times) are not considered in this analysis due to difficulty in

quantifying cost.

6.7.2.1Cost Benefit Analysis

Based on table 6.9 and 6.10, the total cost and benefits are calculated in

table 6.11 and table 6.12 to calculate the economic impacts of function B.

Table 6.11 Cost Benefit Analysis of Function B

Costs Total cost using Alternative 2 $48,503

Driving Cost $8,294

Travel Time $36,864 Remote Problem Solving RFI Processing

Time $14,746 Benefits

Total Benefits $59,904

Benefit to Cost Ratio = $59,904/ $48,503 = 1.23

Net Benefits = $59,904 - $48,503 = $11,401

From the data in table 6.11, the benefits to cost ratio is 1.23 and the total

benefits of function B is $11,401 more than it total cost.

From the data in table 6.12, the benefits to cost ratio is 0.92

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Table 6.12 Cost Benefit Analysis of Function B Costs Total cost using Alternative 2 $81,062

Driving Cost $11,058 Travel Time $49,152

Remote Problem Solving

RFI Processing Time

$14,746 Benefits

Total Benefits $74,956 Benefit to Cost Ratio = $74,956/ $81,062= 0.92 Net Benefits = $74,956 - $81,062= $-6,106

6.7.2.2 Sensitivity and Break-Even Analysis

In this section, sensitivity analysis is conducted to determine the impact of

changing driving distance and frequency of site visit. Three different scenarios

were plotted in terms of one visit per RFIs number. These scenarios include 100,

150 and 200 miles.

Figure 6.15 Cost-Benefit Chart for two Variables

The upper graph shows that with the increase of the distance from the

construction site, the more sensitive to the site visit frequency the results will be.

It also shows a logarithmic increase in total money saved as the number of visits

to site per number of RFIs decreases. From the graph above, we can calculate

$0

$50,000

$100,000

$150,000

$200,000

$250,000

$300,000

$350,000

$400,000

15 12 10 5 1

Visit per RFIs Numbers

Cost

100 miles 150 miles 200 miles Cost

134

the break even of implementing this model just based on the fact of mentioning

the total distance traveled and the number of visit for every RFIs.

To summarize the benefits of this function, we agree on:

• RFIs process will improve providing remote workers a real time tool using

the internet to get access to activities going on construction site.

• With this system, the ability to quickly resolve construction claims and

shorten the time for RFIs will bring other benefits, but these are difficult to

determine.

• Due to the difficulty in assessing indirect and intangible costs, the

economic analysis used in this chapter focus on measuring direct cost and

benefits. However, intangible costs and benefits are equally important and

need more in-depth exploration.

6.7.3 Function C: Wireless Data Access Savings

This function deals with the PEB processes inefficiencies identified in the

previous chapters, and how superintendent, workers, and erectors wasted a lot

of their time to find the right steel parts to be erected, or getting more details of a

steel connection drawings, or even being up to date with steel delivery to the

jobsite and which section in erection will be next. Not able to find the materials to

be used costs more than inconvenience. Time spent searching for assets eats

into productivity, and hence profitability. Workers lose the equivalent of one full

40-hour work week per year if they spend only 10 minutes a day searching for

and gathering needed items. The inability to track materials, or work progress

causes companies to lose money and waste time and be behind schedule.

Based on the information provided in chapter 5 related to measurement of time

required addressing the specific job, especially unloading, shakeout and erection

operation, the following baseline assumptions are formulated for case study 1

and 2.

Table 6.13 Benefits Calculation of Function C Foreman 21%*1920 hours*($36/hour) $14,515 Erectors 21%*1920 hours*($30/hour) $12,096 Workers 21%*1920 hours*($26/hour) $10,483 Total Savings $37,094

135

The other benefits that can be calculated based on this function are work

process elimination and reduce in reworks. That was shown in the work process

flow of the PEB steel structure. Applying the proposed model on the construction

site, eliminate time to stakeout the materials once they are on the jobsite, and

eliminate the need to mark the steel parts again, to identify the parts when

erection starts. Based on measuring the time it took the workers to stakeout the

steel parts, and again to make their own notes to identify the steel parts and

mark them, it was safe enough to make the assumptions that 5% of the total cost

of the project would be saved by implementing function C.

Table 6.14 Rework and Process Elimination Savings for Case study 1 Rework and

Process Elimination

5%*$3,000,000 $150,000

Table 6.15 Rework and Process Elimination Savings for Case study 2

Rework and Process

Elimination 5%*$12,600,000 $630,000

So the total saving gained from function C for case study 1 will be:

Table 6.16 Summary of Benefits of Function C

Improving Efficiency

$37,094

Rework and Process

Elimination $150,000

Total Savings $187,094

So the total saving gained from function C for case study 2 will be:

Table 6.17 Summary of Benefits of Function C Improving Efficiency

$37,094

Rework and Process

Elimination $630,000

Total Savings $667,094

136

6.7.3.1 Cost Benefit Analysis

Based on table 6.16, the total cost and benefits are calculated in table

6.18 to calculate the economic impacts of function C for case study 1.

Table 6.18 Cost Benefit Analysis of Function C

Costs Total cost using Alternative 2 $48,503

Efficiency $37,094 Improve

Efficiency &

Processes

Rework and

Process

Elimination

$150,000

Benefits

Total Benefits $187,094

Benefit to Cost Ratio = $187,094/ $48,503 = 3.86

Net Benefits = $187,094- $48,503 = $138,591

From the data in table 6.18, the benefits to cost ratio is 3.86 and the total

benefits of function C is $138,591 more than it total cost.

Based on table 6.17, the total cost and benefits are calculated in table

6.18 to calculate the economic impacts of function C for case study 1.

Table 6.19 Cost Benefit Analysis of Function C

Costs Total cost using Alternative 2 $57,983

Efficiency $37,094 Improve Efficiency & Processes

Rework and Process Elimination

$630,000

Benefits

Total Benefits $667,094

Benefit to Cost Ratio = $667,094/ $81,062= 8.22 Net Benefits = $667,094- $81,062= $586,032

From the data in table 6.19, the benefits to cost ratio is 8.22 and the total

benefits of function C is $586,032 more than it total cost.

137

6.7.4 Function D: E-Document Management Savings

This function addresses bottleneck in the shop drawing approval process

of structural steel construction. The submittal log maintained five shop drawing

packages between Sperry and Associates and American Building Company

during the shop drawing approval stage. Using e-drawing will accelerate the

process of drawing moving from one party to another and the work flow will be

much faster. So if a modification is required, it can be completed on line and sent

to the next party involved in the approval process in real time.

The costs for a traditional paper based document delivery are calculated

based on the following assumptions:

• Five sets of drawings are reproduced by the steel supplier

• Plan-printing price for one set of drawings (30 sheets) is $65

• Typical UPS rate associated with sending a 20Lbs tube of drawing

package to each party involved in the approval process is $80

Table 6.20 Benefits Calculation of Function D Printing Cost 10 drawing packages

*5 set *($65/set of drawings)

$3,250 Traditional Paper-Based Approach Delivery Cost 10 drawing packages *5

set * ($80/set of drawings $4,000

Total Cost $7,250

Once we identified the benefits occurred from each function

independently, the next step is to add all benefits together to get the total benefits

that the model will bring to the construction site. The summary of all benefits is

shown in table 6.21 for case study 1 and in table 6.22 for case study 2.

Table 6.21 Summary of Benefits Site Inspection $7,603 Problem Solving $59,904 Sensing & Data Access $187,094 E-Document Management $7,250

Total Savings = $261,851 - $48,503 $213,348 (7.11%)

138

The total savings is $213,348, which represents roughly 7% of the total

cost of the project. Implementing the proposed model will result in at least

additional 7% in profit. This was based only on direct savings.

Table 6.22 Summary of Benefits Site Inspection $9,801 Problem Solving $74,956 Sensing & Data Access $667,094 E-Document Management

$7,250

Total Savings = $759,101 - $81,062 $678,039 (5.5%)

The total savings is $678,039, which represents roughly 5.5% of the total

cost of the project. Implementing the proposed model will result in at least

additional 5.5% in profit. This was based only on direct savings.

139

CHAPTER 7

CONCLUSIONS AND RECOMMENDATION

This dissertation proposed a framework for real-time project progress

tracking and a utility function model for wireless technology evaluation and

selection. This chapter summarizes the research and highlights the research

contributions. Subsequently the limitations of the research are discussed. Finally,

recommendations for future work are provided.

7.1 Summary of the research

The construction industry suffers from stagnant productivity, project

delays, quality problems and resistance to new technologies. Research studies

have shown that the major cause of the problems can be traced back to the lack

of effective communication among construction process units. One commonly

cited means to overcome this problem is through the use of advance

technologies. But the challenge arises when decision to choose the best

technology to fulfill the need because each system has its own technical,

economic, and risk considerations.

The goal of this research was to develop a model that helps decision

makers to choose the best information technology that fits their needs. The

model employed multiple-attribute utility functions for implementing a collective

approach to assess information technology alternatives into construction project.

Herein, utility functions provided a universal platform for integrating several

predefined measures of information technology into a single indicator of such

performance. To achieve that, a survey was performed to determine construction

people preferences for proposed attributes. Then single utility function are

integrated together to form the multiple attribute utility function. Then proposed

140

alternatives were tested in the evaluation model to determine the best alternative

to be used in our case studies.

Then the research proposed a framework for a real-time model for project

progress tracking. The basic premise of the proposed model is to network

previously stand alone islands of communication on a construction site to allow

for the network between different parties involved in the construction project. So

a database was developed to show where the information will be stored, how

they can be retrieved, and how the progress of the activities is implemented in

the master schedule to keep all parties updated.

Then two case studies were used to highlight the values of implementing

such model on the construction site. That was achieved first by studying the

construction process, developing flow diagram, and then performing simulation

analysis to determine productivity before and after implementing the real-time

project progress-tracking model.

7.2 Research Contribution

The contributions of this research include:

• A framework for tracking construction project using wireless technologies and

database management system is developed. The model integrates RFID with

mobile computing technology and wireless technologies to increase the

efficiency and accuracy of the jobsite data collection and schedule update.

There has been some previous research works that utilize this kind of

technology on construction site to track materials and equipments locations.

The real-time progress tracking model not only tracks materials, labors and

equipment of construction site, but it also updates the project schedule

instantly as soon as the activity occurs.

• Furthermore, a central database management system is developed to act as

a storage room for the information sent. At the same time this database plays

the role of a library to get the required information while on the construction

141

site and not able to access the site office. Simple queries using SQL are

presented to represents some of the information needs on the construction

site.

• This research identifies the need to improve construction site efficiency by

implementing information technology. Barriers to implementation of such

systems on construction site are identified. Some of the barriers are lack of

assessment method to incorporate different criteria in the user judgment and

lack of metrics to assess benefits. So the need to a decision support tool and

a clear benefit assessment metrics arises.

• A hybrid decision support model for real-time project tracking model selection

is developed. The model applies principles from multi-attribute decision theory

to help decision makers to select and evaluate the appropriate information

technology for the required construction application. This model is based on

analytic hierarchy process that applied eigenvector method to determine the

users’ preferences. The model evaluates each proposed criteria and give it a

utility function value. The alternative with the highest utility value corresponds

to the best alternative that fulfills the need. With small modifications, the

hybrid decision model can be used to assess other can of goals by just

modifying the required attributes for assessment.

• For models implementation, two steel construction projects were used as

examples for the proposed models. An information flow diagram, followed by

simulation model for Pre-Engineered process from shipping the steel

materials till erection on the construction site was developed. Then a

feasibility study of implementing the proposed project tracking model and its

impact on the construction project was conducted. Because the multifaceted

benefits of the various applications, different scientific methods were used to

measure the value that the technology integrated model will incorporate into

the construction process.

142

7.3 Limitations

The utility function model developed in this study provides a

comprehensive approach to assess information technology that can be used on

construction site to update project progress. However, there are some limitations

in the present model, especially regarding the assumption made for the utility risk

attitude. Although the attributes developed cover the majority of users concerns,

but these attribute may change if the main objective changes. Establishing

priorities between attribute is also an obstacle because of lack of enough data

and people in the construction industry that are willing to spend sometime on

taking a survey.

Although the framework for real time project progress tracking suggested

a full monitoring of resources such as equipment material and labors. This study

was just limited to materials and especially to pre-engineered steel parts because

of the limited data we were able to collect from the construction sites.

The quantification of benefits is based on theoretical background and

related research project. The proposed model needs to be implemented in a real

case study to strengthen the conclusions regarding application of wireless

technologies on the construction site.

7.4 Recommendations for Future Work

The construction industry is very conservative, and will only adopt new

information technologies if they are simple to implement, and provide immediate

benefits. Hopefully, the value assessment study we included in this thesis will

open the window for real time tracking using information technology.

The model presented in this research should be fully developed by writing

a computer program to link Microsoft project and Microsoft Access, and then link

Microsoft Access to the RFID software. It is recommended that a pilot project be

conducted by construction companies looking to invest in the proposed model

before completely changing the current process. If the pilot project is a success

143

and the company wants to implement this change for all future projects, then

further effort should go into planning and research to ensure that a smoothly

running system is being developed.

The survey developed in this survey should be continued by getting a

bigger population size. At the end the bigger the population is, the better the level

of confidence and the less the margin of error allowed.

This research only attempted to evaluate two categories of hardware

computing and wireless connection. Future work should include more categories

like wearable computers.

144

APPENDIX A

SMART CHIPS

Linear barcode

This is the most common barcode type and is composed of a series of

parallel and varying width of bars and spaces (see figure 3.2). These bars work

as the license plate data holders, typically hold 10 to 20 characters, where they

direct the user to information stored in the host computer database.

One Dimension Barcode Source: (http://www.taltech.com/resources/intro_to_bc/bcsymbol.htm)

Stacked

In this type, short individual linear barcodes are stacked on the top of each

other (see figure 3.3). This stack barcodes store relatively a large amount of data

(up to 1000 characters) along the height of the code. The most successful

symbology is the portable data file (PDF 417) in which a series of data items can

be linked together in one single database (Cohen 1994). However, stacked

barcodes is not as efficient as the matrix barcodes in terms of space efficiency.

Stacked Barcode Source: (http://www.taltech.com/resources/intro_to_bc/bcsymbol.htm)

145

Matrix barcodes (Two-dimensional)

The need to increase the data capacity and information density of barcode

symbologies triggered several efforts to drive the development of the two

dimensional barcodes. The matrix symbology comprises a matrix of light and

dark elements, circles, squares, or hexagons (see figure 3.4). In construction

industry, two-dimensional barcode is suitable for keeping construction records

such as equipment maintenance records

Matrix Barcodes Source: (http://www.taltech.com/resources/intro_to_bc/bcsymbol.htm)

Difference between Barcode and RFID Technologies

System Barcode RFID

Data Transmission Optical Electromagnetic

Typical Data Volume

Data Modification

1-100 Bytes

Not possible

128-8k Bytes

Possible

Position of Data Carrier for

Read/Write

Visual contact

Not possible

Non line of sight

Possible

Reading Distance Several meters From centimeters to meters

Access Security Little High

Anti-collision Not possible Possible

146

Global RFID tag classification Class 0 Passive Factory programmable (64 bit only)

Class 1 Passive WORM with provisions for read/write (96

bit min.)

Class 2 Passive Short range (4”-18”), R/W multiple, user

memory

Class 3 Battery Assisted reader

activates, battery powers

Medium range (10’-50’), R/W. user

memory, sensors, encryption

Class 4 Active – battery powered Long range (300’), user memory, sensors…

147

148

Passive RFID Tag

149

150

Handheld RFID Reader

151

Jobsite Information Needs (adapted from de la Garza and Howitt 1998) 1. Request for Information (RFI)

Design intent and clarification Subcontractor information Contract specifications Contract drawings Work package information Means and methods Implementation problems

2. Materials Management Access to material management Material location Material order status Request materials to site Place material orders

3. Equipment Management Equipment location Fuel monitoring

4. Cost Management Budget Material cost accounting Equipment cost accounting

5. Schedule and Means and Methods Schedule updates Delay recording As-built records Productivity information

6. Jobsite Record Keeping Recording timesheets Progress reporting Exception reporting Visitors log

7. Submittals Test results Revisions to submittals

8. Safety Accident reporting Reporting violations

9. QC/QA Initiate inspections Report QC/QA problems Report inspections results

10. Future Trends Positioning data Sensory data

152

APPENDIX B

SURVEY

Because of your strong expertise in the construction industry and/or information technologies, we would be grateful if you could respond to the attached survey. This survey is part of an industry-oriented research project conducted at Florida State University, U.S.A., under the supervision of Doctor Y. AbdelRazig.

The survey focuses on the evaluation of existing information technology such as PDA’s, tablet PC’s, RFID, wireless communication to be used on the construction site to track the progress of construction project. The determination of usefulness will be based of on the preferences of professionals like yourself in using the available technologies to bridge the stand alone island of communication on the construction site. The basic criteria for evaluation are presented based on a thorough literature review. The results of this survey will be ultimately used to develop an evaluation tool for information technologies in the construction industry.

It will take you about 15-20 minutes to answer the questionnaire. Your participation will be most appreciated and your responses will not be released to any other parties without your consent.

To take the survey, click the link below http://www.eng.fsu.edu/~ghaneam

Regards,

Amine Ghanem, Ph.D. Candidate Email: [email protected] FAMU-FSU College of Engineering

153

Informed Consent

This survey is being conducted by Amine Ghanem, a graduate student with Florida State

University's College of Engineering, as research for his thesis on assessing the feasibility

of implementing wireless technologies in construction. Dr. Yassir AbdelRazig is the

Graduate Advisor for this student, and will be the professor overseeing this research.

Your participation in this research is voluntary, and consists of filling a series of online

tables about user preferences that will take approximately 20 minutes. By law, you must

be 18 years old or older to participate in this research. By submitting your survey you are

indicating your consent to participate, and that you are at least 18 years old. You may

withdraw consent at any point by closing the Web page before completing and submitting

the survey. There will be no penalty for non-participation. All answers will be kept

completely anonymous, and information obtained during the course of the study will

remain confidential to the extent allowed by law.

If you are uncomfortable supplying your name, email address, and company name, you

may complete the survey without including this data.

If you are interested in receiving the final results please provide us with your name and

email address at the end of the survey.

If you have any questions about your rights as a subject for this research you may contact

the Chair of the Human Subjects Committee, Institutional Review Board, at 850-644-

8633. If you have any questions regarding this research please contact Amine Ghanem

by email at [email protected] or by phone 850-410-6211. Dr. AbdelRazig can be reached at

[email protected].

Section 1: General Information

Name *

Email Address *

Company Name *

Education Level

Experience

Position

* Optional fields

154

Section 2: Setting Priorities

Please assign a weight from 1 to 9 based on the relative importance of one element over

another with respect to the criteria. Please refer to the table below for the degree of

importance

Degree of Importance

Definition Explanation

1 Equal importance Two elements contribute equally to the property

3 Moderate importance

Experience and judgment slightly favor one element over another

5 Strong importance

Experience and judgment strongly favor one element over another

7 Very strong importance

An element is strongly favored and its dominance is demonstrated in practice

9 Extreme importance

The evidence favoring one element over another is of the highest possible order of affirmation

2,4,6,8 Intermediate values between two adjacent degrees of importance Compromise is need between two judgments

• Remember that the element that appears in the left hand column is always

compared with the element appearing in the top row

• For example if technological criteria is 4 times more important than economic

criteria, put 4 in the appropriate box and if economic criteria is 3 time less

important than risk criteria put 1/3 in the appropriate box as shown in the table

below:

Technological Economic Risk

Technological 1 4

Economic 1 1/3

Risk 1

155

1) Please fill the table below with the degree of importance in order to fulfill a real

time project progress tracking

2) Please fill the table below with the degree of importance in order to fulfill the

technological importance

Technical

Requirement

Skills

Accuracy Rugged

Characteristic

Screen

dimension

Battery

life

Weight

including

Battery

Writing

Ability

Software

Accommodation

Wireless

Connection

Speed

Technical

Requirement

Skills 1

Accuracy 1

Rugged Characteristic

1

Screen

dimension 1

Battery life 1

Weight

including

Battery

1

Writing Ability 1

Software

Accommodation 1

Wireless

Connection

Speed

1

3) Please fill the table below with the degree of importance in order to fulfill the

economical importance

Initial

Investment

Operating

Cost

Saving in

Labor

Quality

Improvement

Initial

Investment 1

Operating

Cost 1

Saving in

Labor 1

Quality

Improvement 1

Technological Economic Risk

Technological 1

Economic 1

Risk 1

156

4) Please fill the table below with the degree of importance in order to fulfill the risk

importance?

Equipment

Reliability

Performance

Reliability

Investment

Risk Security

Equipment

Reliability 1

Performance

Reliability 1

Investment

Risk 1

Security 1

Section 3: Determining Utilities

Identify the degree of liking for the possible values that can be associated with each

attribute. UL represents the value where the degree of liking reaches zero, while UH

represents the value where the degree of liking reaches its ultimate level of 1.0

Attributes Measures UL UH

Technical

Requirement Skills

Moderate/Satisfactory Very Low Very Low

Accuracy Low/high Very Low Very Low Rugged Characteristic IP00 IP00 IP00

Screen dimension inches 2 2

Battery life Hours 1 1

Weight including

Battery

Lb 0.5 0.5

Writing Ability Typing/Touching Typing Typing

Software

Accommodation

CAD/Project

Management/Both

None None

Wireless

Connection Speed

kbps- Mbps 14Kb 14Kb

Initial Investment % of Project Total

Cost

0.25% 0.25%

Operating Cost % of Project Total

Cost

0.25% 0.25%

Saving in Labor Satisfactory/moderate Very Unsatisfactory Very Unsatisfactory

Quality

Improvement

Satisfactory/moderate Very Unsatisfactory Very Unsatisfactory

Equipment

Reliability

Low/High Very Low Very Low

Performance

Reliability

Low/High Very Low Very Low

Investment Risk Low/High Very Low Very Low

Security Y/N Yes Yes

157

Thank you very much for your willingness to participate in this short survey. If you

are interested in receiving the final result please provide us with your information

below:

Name

Email Address

158

Ingress Protection Rating Explanation

CAD CAD (computer-aided design) software is used by architects,

engineers, drafters, artists, and others to create precision drawings

or technical illustrations. CAD software can be used to create two-

dimensional (2-D) drawings or three-dimensional (3-D) models. Information Technology IT (information technology) is a term that encompasses all forms of

technology used to create, store, exchange, and use information in its various

forms (business data, voice conversations, still images, motion pictures,

multimedia presentations, and other forms, including those not yet

conceived). It's a convenient term for including both telephony and computer

technology in the same word. It is the technology that is driving what has

often been called "the information revolution." PDA Abbreviation for Personal Data Assistance. It refers to a handheld computer Tablet PCs A Tablet PC is a computer shaped in the form of a notebook or a slate with

the capabilities of being written on through the use of digitizing tablet

technology or a touch screen. A user can use a stylus and operate the

computer without having to have a keyboard or mouse Wireless Communication Wireless is a term used to describe telecommunications in which

electromagnetic waves (rather than some form of wire) carry the signal over

part or all of the communication paths. RFID Radio Frequency Identification is an automatic identification method,

relying on storing and remotely retrieving data using devices called RFID

tags or transponders. An RFID tag is an object that can be attached to or

incorporated into a product, animal, or person for the purpose of

identification using radio waves. Chip-based RFID tags contain silicon chips

and antennae. Passive tags require no internal power source, whereas active

tags require a power source.

159

Minimum Sample Size of a Population

160

APPENDIX C

CASE STUDY DOCUMENTS

Case Study 1 Files

Turbocore Master Schedule

161

Different Phases of the Project

162

Pre-Engineered Building Elevation

163

Pre-Engineered Building Elevation Continue

164

Plan of the Pre-Engineered Building

165

Bill of Materials

166

Bill of Materials Continue

167

Bill of Materials Continue

168

Case Study 2 Files

Different Phases of the Project

169

Different Phases of the Project

170

Master Schedule

171

Master Schedule Continue

172

Master Schedule Continue

173

Master Schedule Continue

174

Master Schedule Continue

175

Master Schedule Continue

176

APPENDIX D

SIMULATION INPUT/OUTPUT FILES

Results: STEEL SHIPPING

STEEL SHIPPING

PRODUCTIVITY INFORMATION

Total Sim. Time Unit Cycle No. Productivity (per time unit)

107.3 30 0.27954059805008047

STEEL SHIPPING

CYCLONE ACTIVE ELEMENTS STATISTICS

INFORMATION

Activity

Type No. Name

Access

Counts

Average

Duration

Maximum

Duration

Minimum

Duration

COMBI 2 LOAD

MATERIALS 31 3.4 5.4 1.0

NORMAL 3 TRAVEL TO

JOB 29 7.5 10.4 4.2

COMBI 7 OFF-LOAD

MATERIALS 31 1.9 3.9 0.0

NORMAL 8 TRAVEL

BACK 30 7.5 10.4 4.2

STEEL SHIPPING

CYCLONE PASSIVE ELEMENTS STATISTICS

INFORMATION

Type No. Name

Average

Units

Idle

Max.

Idle

Units

Times

not

empty

% Idle

Total

Sim

Time

Average

Wt

Time

Units

at

end

QUEUE 1 STEEL

BATCH 0.0 1 0.0 0.00 107.3 0.0 0

177

QUEUE 4 WAIT TO

OFF-LOAD 0.1 3 12.3 11.43 107.3 0.4 0

QUEUE 5 CREW

AVAILABLE 0.4 1 46.7 43.55 107.3 1.4 0

QUEUE 6 CRANE

AVAILABLE 0.4 1 46.7 43.55 107.3 1.4 0

QUEUE 10 TRUCK

QUEUE 3.1 6 107.3 100.00 107.3 8.1 4

Shipping Simulation Output Files

178

Results: PROPOSED STEEL SHIPPING

STEEL SHIPPING TO BE

PRODUCTIVITY INFORMATION

Total Sim. Time Unit Cycle No. Productivity (per time unit)

67.1 30 0.4471830100933253

STEEL SHIPPING

CYCLONE ACTIVE ELEMENTS STATISTICS

INFORMATION

Activity

Type No. Name

Access

Counts

Average

Duration

Maximum

Duration

Minimum

Duration

COMBI 3 LOAD

MATERIALS 33 1.3 2.7 0.0

NORMAL 4 TRAVEL TO

JOB 31 7.6 10.4 4.2

COMBI 8 OFF-LOAD

MATERIALS 33 1.3 2.7 0.0

NORMAL 9 TRAVEL

BACK 30 7.6 10.4 4.2

STEEL SHIPPING

CYCLONE PASSIVE ELEMENTS STATISTICS

INFORMATION

Type No. Name

Average

Units

Idle

Max.

Idle

Units

Times

not

empty

%

Idle

Total

Sim

Time

Average

Wt

Time

Units

at

end

QUEUE 1 RFID TAGS

AVAILABLE 0.3 1 23.0 34.31 67.1 0.7 0

QUEUE 2 STEEL

AVAILABLE 0.3 1 23.0 34.31 67.1 0.7 0

QUEUE 5 WAIT TO 0.3 3 15.8 23.56 67.1 0.5 0

179

OFF-LOAD

QUEUE 6 CREW

AVAILABLE 0.3 1 23.2 34.58 67.1 0.7 0

QUEUE 7 CRANE

AVAILABLE 0.3 1 23.2 34.58 67.1 0.7 0

QUEUE 11 TRUCK

QUEUE 0.4 6 15.6 23.26 67.1 0.6 2

Proposed Shipping Simulation Output Files

180

Results: STEEL ERECTION

STEEL ERECTION

PRODUCTIVITY INFORMATION

Total Sim. Time Unit Cycle No. Productivity (per time unit)

2155.9 300 0.13915594220655672

STEEL ERECTION

CYCLONE ACTIVE ELEMENTS STATISTICS

INFORMATION

Activity

Type No. Name

Access

Counts

Average

Duration

Maximum

Duration

Minimum

Duration

COMBI 7

SPACING

& RIGHT

UP

ELEMENT

303 3.0 6.2 0.0

COMBI 9 LIFT

COLUMN 1202 1.0 3.3 0.0

COMBI 12 PLACE

COLUMN 1202 0.5 1.9 0.0

COMBI 15

CONNECT

COLUMN

TO A.B.

1201 0.5 1.9 0.0

COMBI 19 CONNECT

GIRDERS 604 1.5 4.7 0.0

COMBI 22 ERECT

GIRDERS 604 2.0 5.2 0.0

COMBI 26 INSTALL

BRACING 301 3.0 6.2 0.0

COMBI 29

INSTALL

PURLINS

AND

GIRTS

300 3.0 6.2 0.0

181

STEEL ERECTION

CYCLONE PASSIVE ELEMENTS STATISTICS

INFORMATION

Type No. Name

Average

Units

Idle

Max.

Idle

Units

Times

not

empty

%

Idle

Total

Sim

Time

Average

Wt

Time

Units

at

end

QUEUE 4 STEEL AVAIL 0.2 4 315.3 14.63 2155.9 1.1 1

QUEUE 5 CRANE IDLE 0.0 1 0.2 0.01 2155.9 0.0 0

QUEUE 6 WORKERS

IDLE 1.0 2 2154.7 99.95 2155.9 1.4 1

GEN 8 COLUMNS

AVAILABLE 15.1 27 2149.5 99.71 2155.9 26.9 13

QUEUE 10

ANCHOR

BOLTS

CASTED IN

PLACE

0.0 1 0.6 0.03 2155.9 0.0 0

QUEUE 11 WORKERS

IDLE 3.0 4 2142.2 99.37 2155.9 2.4 2

QUEUE 13 WAIT TO FIX 0.0 2 8.7 0.41 2155.9 0.0 0

QUEUE 14 CONNECTOR

IDLE 1.7 2 2092.6 97.06 2155.9 3.0 1

GEN 17 GIRDERS

AVAIL 0.1 4 152.4 7.07 2155.9 0.3 0

QUEUE 18 CONNECTORS

IDLE 1.0 2 1492.4 69.22 2155.9 1.8 2

QUEUE 20

WAIT TO

CONNECT

GIRDER TO

COLUMNS

0.7 8 779.0 36.13 2155.9 2.6 0

QUEUE 21 CRANE IDLE 0.4 1 938.6 43.54 2155.9 1.6 1

QUEUE 24 BRACING

AVAIL 0.0 1 0.0 0.00 2155.9 0.0 0

QUEUE 25 WORKERS

IDLE 1.6 2 2123.7 98.51 2155.9 11.2 1

QUEUE 27

PURLINS AND

GIRTS

AVAILABLE

0.1 2 122.8 5.70 2155.9 0.4 0

182

QUEUE 28 FORKLIFT

IDLE 0.6 1 1260.4 58.46 2155.9 4.2 0

Erection Simulation Output Files

183

PROPOSED STEEL ERECTION

PRODUCTIVITY INFORMATION

Total Sim. Time Unit Cycle No. Productivity (per time unit)

1699.3 300 0.17654286547624465

STEEL ERECTION

CYCLONE ACTIVE ELEMENTS STATISTICS

INFORMATION

Activity

Type No. Name

Access

Counts

Average

Duration

Maximum

Duration

Minimum

Duration

COMBI 7

SPACING

& RIGHT

UP

ELEMENT

303 1.5 3.8 0.0

COMBI 9 LIFT

COLUMN 1199 1.0 3.3 0.0

COMBI 12 PLACE

COLUMN 1199 0.5 1.9 0.0

COMBI 15

CONNECT

COLUMN

TO A.B.

1198 0.5 1.9 0.0

COMBI 19 CONNECT

GIRDERS 602 1.5 4.7 0.0

COMBI 22 ERECT

GIRDERS 600 1.5 3.8 0.0

COMBI 26 INSTALL

BRACING 300 2.0 4.3 0.0

COMBI 29

INSTALL

PURLINS

AND

GIRTS

300 2.0 4.3 0.0

184

STEEL ERECTION

CYCLONE PASSIVE ELEMENTS STATISTICS

INFORMATION

Type No. Name

Average

Units

Idle

Max.

Idle

Units

Times

not

empty

%

Idle

Total

Sim

Time

Average

Wt

Time

Units

at

end

QUEUE 4 STEEL AVAIL 0.1 4 237.3 13.96 1699.3 0.8 1

QUEUE 5 CRANE IDLE 0.0 1 0.0 0.00 1699.3 0.0 0

QUEUE 6 WORKERS

IDLE 1.0 2 1698.5 99.95 1699.3 1.1 1

GEN 8 COLUMNS

AVAILABLE 16.4 27 1698.5 99.95 1699.3 23.1 16

QUEUE 10

ANCHOR

BOLTS

CASTED IN

PLACE

0.0 1 0.7 0.04 1699.3 0.0 0

QUEUE 11 WORKERS

IDLE 2.9 4 1689.1 99.40 1699.3 1.8 3

QUEUE 13 COLUMN

PLACED 0.0 2 10.0 0.59 1699.3 0.0 0

QUEUE 14 CONNECTOR

IDLE 1.6 2 1634.9 96.21 1699.3 2.3 1

GEN 17 GIRDERS

AVAIL 0.1 4 119.9 7.06 1699.3 0.2 0

QUEUE 18 CONNECTORS

IDLE 0.9 2 1071.6 63.06 1699.3 1.3 1

QUEUE 20 GIRDER

CONNECTED 0.5 8 502.1 29.55 1699.3 1.4 1

QUEUE 21 CRANE IDLE 0.5 1 791.9 46.60 1699.3 1.3 0

QUEUE 24 BRACING

AVAIL 0.0 1 0.0 0.00 1699.3 0.0 0

QUEUE 25 WORKERS

IDLE 1.6 2 1679.9 98.86 1699.3 9.2 2

QUEUE 27

PURLINS AND

GIRTS

AVAILABLE

0.0 2 50.5 2.97 1699.3 0.2 0

QUEUE 28 FORKLIFT 0.6 1 1102.4 64.87 1699.3 3.7 1

185

IDLE

Proposed Erection Simulation Output Files

186

Input Files

NAME STEEL SHIPPING LENGTH 1000 CYCLES 30

NETWORK INPUT

1 QUE 'STEEL BATCH'

2 COM SET 1 'LOAD MATERIALS' FOL 1 3 PRE 1 10

3 NOR 'TRAVEL TO JOB' SET 2 FOL 4

4 QUE 'WAIT TO OFF-LOAD'

5 QUE 'CREW AVAILABLE'

6 QUE 'CRANE AVAILABLE'

7 COM SET 3 'OFF-LOAD MATERIALS' FOL 5 6 8 PRE 4 5 6

8 NOR 'TRAVEL BACK' SET 4 FOL 9

9 FUN COU FOL 10 QUA 1

10 QUE 'TRUCK QUEUE'

DURATION INPUT

SET 1 NOR 3 1

SET 2 NOR 7 2

SET 3 NOR 1.5 1

SET 4 NOR 7 2

RESOURCE INPUT

1 'STEEL BATCH' AT 1

3 'TRUCK' AT 4

1 'CREW' AT 5

1 'CRANE' AT 6

6 'TRUCKS' AT 10

ENDDATA

Shipping Input Model

NAME STEEL ERECTION LENGTH 2000000 CYCLE 300

NETWORK INPUT

4 QUE 'STEEL AVAIL'

5 QUE 'CRANE IDLE'

6 QUE 'WORKERS IDLE'

7 COM 'SPACING & RIGHT UP ELEMENT' SET 6 PRE 4 5 6 FOL 5 6 8

8 QUE 'COLUMNS AVAILABLE' GEN 4

9 COM 'LIFT COLUMN' SET 9 PRE 5 6 8 FOL 5 6 10

10 QUE 'ANCHOR BOLTS CASTED IN PLACE'

11 QUE 'WORKERS IDLE'

12 COM 'PLACE COLUMN' SET 12 PRE 10 11 FOL 11 13

13 QUE 'WAIT TO FIX'

14 QUE 'CONNECTOR IDLE'

15 COM 'CONNECT COLUMN TO A.B.' SET 16 PRE 11 13 14 FOL 11 14 16

16 FUN CON 4 FOL 17

17 QUE 'GIRDERS AVAIL' GEN 2

18 QUE 'CONNECTORS IDLE'

187

19 COM 'CONNECT GIRDERS' SET 18 PRE 17 18 FOL 18 20

20 QUE 'WAIT TO CONNECT GIRDER TO COLUMNS'

21 QUE 'CRANE IDLE'

22 COM 'ERECT GIRDERS' SET 22 PRE 18 20 21 FOL 18 21 23

23 FUN CON 2 FOL 24

24 QUE 'BRACING AVAIL'

25 QUE 'WORKERS IDLE'

26 COM 'INSTALL BRACING' SET 25 PRE 24 25 FOL 25 27

27 QUE 'PURLINS AND GIRTS AVAILABLE'

28 QUE 'FORKLIFT IDLE'

29 COM 'INSTALL PURLINS AND GIRTS ' SET 28 PRE 11 27 28 FOL 11 28 30

30 FUN COU FOL 4 QUA 1

DURATION INPUT

SET 6 NOR 3 1

SET 9 NOR 1 0.5

SET 12 NOR 0.5 0.2

SET 16 NOR 0.5 0.2

SET 18 NOR 1.5 1

SET 22 NOR 2 1

SET 25 NOR 3 1

SET 28 NOR 3 1

RESOURCE INPUT

4 'COLUMN' AT 4

1 'CRANE' AT 5

2 'WORKERS' AT 6

1 'COLUMN' AT 8

4 'ERECTORS' AT 11

2 'CONNECTORS' AT 14

2 'GIRDERS' AT 17

2 'CONNECTORS' AT 18

1 'CRANE' AT 21

2 'WORKERS' AT 25

1 'FORKLIFT' AT 28

ENDDATA

Erection Input Model

NAME STEEL SHIPPING LENGTH 1000 CYCLES 30

NETWORK INPUT

1 QUE 'RFID TAGS AVAILABLE'

2 QUE 'STEEL AVAILABLE'

3 COM SET 1 'LOAD MATERIALS' FOL 1 2 4 PRE 1 2 11

4 NOR 'TRAVEL TO JOB' SET 2 FOL 5

5 QUE 'WAIT TO OFF-LOAD'

6 QUE 'CREW AVAILABLE'

7 QUE 'CRANE AVAILABLE'

8 COM SET 3 'OFF-LOAD MATERIALS' FOL 6 7 9 PRE 5 6 7

188

9 NOR 'TRAVEL BACK' SET 4 FOL 10

10 FUN COU FOL 11 QUA 1

11 QUE 'TRUCK QUEUE'

DURATION INPUT

SET 1 NOR 1 0.5

SET 2 NOR 7 2

SET 3 NOR 1 0.5

SET 4 NOR 7 2

RESOURCE INPUT

1 'RFID Tags' AT 1

1 'STEEL BATCH' AT 2

3 'TRUCK' AT 5

1 'CREW' AT 6

1 'CRANE' AT 7

6 'TRUCKS' AT 11

ENDDATA

Proposed Shipping Input Model

NAME STEEL ERECTION LENGTH 2000000 CYCLE 300

NETWORK INPUT

4 QUE 'STEEL AVAIL'

5 QUE 'CRANE IDLE'

6 QUE 'WORKERS IDLE'

7 COM 'SPACING & RIGHT UP ELEMENT' SET 6 PRE 4 5 6 FOL 5 6 8

8 QUE 'COLUMNS AVAILABLE' GEN 4

9 COM 'LIFT COLUMN' SET 9 PRE 5 6 8 FOL 5 6 10

10 QUE 'ANCHOR BOLTS CASTED IN PLACE'

11 QUE 'WORKERS IDLE'

12 COM 'PLACE COLUMN' SET 12 PRE 10 11 FOL 11 13

13 QUE 'COLUMN PLACED'

14 QUE 'CONNECTOR IDLE'

15 COM 'CONNECT COLUMN TO A.B.' SET 16 PRE 11 13 14 FOL 11 14 16

16 FUN CON 4 FOL 17

17 QUE 'GIRDERS AVAIL' GEN 2

18 QUE 'CONNECTORS IDLE'

19 COM 'CONNECT GIRDERS' SET 18 PRE 17 18 FOL 18 20

20 QUE 'GIRDER CONNECTED'

21 QUE 'CRANE IDLE'

22 COM 'ERECT GIRDERS' SET 22 PRE 18 20 21 FOL 18 21 23

23 FUN CON 2 FOL 24

24 QUE 'BRACING AVAIL'

25 QUE 'WORKERS IDLE'

26 COM 'INSTALL BRACING' SET 25 PRE 24 25 FOL 25 27

27 QUE 'PURLINS AND GIRTS AVAILABLE'

28 QUE 'FORKLIFT IDLE'

29 COM 'INSTALL PURLINS AND GIRTS ' SET 28 PRE 11 27 28 FOL 11 28 30

189

30 FUN COU FOL 4 QUA 1

DURATION INPUT

SET 6 NOR 3 1

SET 9 NOR 1 0.5

SET 12 NOR 0.5 0.2

SET 16 NOR 0.5 0.2

SET 18 NOR 1.5 1

SET 22 NOR 2 1

SET 25 NOR 3 1

SET 28 NOR 3 1

RESOURCE INPUT

4 'COLUMN' AT 4

1 'CRANE' AT 5

2 'WORKERS' AT 6

1 'COLUMN' AT 8

4 'ERECTORS' AT 11

2 'CONNECTORS' AT 14

2 'GIRDERS' AT 17

2 'CONNECTORS' AT 18

1 'CRANE' AT 21

2 'WORKERS' AT 25

1 'FORKLIFT' AT 28

ENDDATA

Proposed Erection Input File

190

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198

BIOGRAPHICAL SKETCH

EDUCATIONAL BACKGROUND

Ph.D. in Civil Engineering (Construction Management), Florida State University,

Tallahassee FL, (Summer 2007)

Dissertation: A Framework for Real-time Construction Project Progress Tracking

Cumulative GPA 4.0

Advisor: Dr. Yassir AbdelRazig

Areas of specialization: Wireless Technologies, Smart Chips, RFID, Bar Codes,

Scheduling and Project Control, Estimation, Project Management,

Risk Analysis.

M.S. in Civil Engineering (Construction Management), Oklahoma State University,

Stillwater, Ok 2002

Cumulative GPA 4.0

Advisor: Dr. Garold Oberlender & Dr. Rock Spencer

Graduation Project: Six Sigma in Construction

B.S. in Civil Engineering (Construction Management) Beirut Arab University,

Lebanon 2001

Cumulative GPA 3.2/4.0

Advisor: Dr. Waleed Chatila

Graduation Project: Management and Rehabilitation of an existing building

SUMMARY OF EXPERTISE

� Project Management

� Construction Estimation

� Information Technologies in Construction

� Project Control and Scheduling

� Simulation Model

� Risk Analysis

� Cost Benefit Analysis

� Applications of GIS in transportation systems

199

PROFESSIONAL CERTIFICATIONS

Registered Professional Engineer in Lebanon, June 2001

RESEARCH / PROFESSIONAL EXPERIENCE

Florida State University, Tallahassee, FL 2004-to date

Research Assistant Works involved building an Integrated Wireless Communication Model for Construction

Projects and conduct a cost benefit analysis of the model.

Oklahoma State University, Stillwater, OK, summer 2002

Research Assistant

Works involved Highways Technology, Computer Programming

Oklahoma State University, Stillwater, OK, spring 2002

Research Assistant

Work involved Computer Programming, CPM method, Linear Schedule

Arabian Construction Company (ACC), Tripoli, Lebanon, summer 2000

Internship (Site Engineer)

Supervising the construction of three buildings, providing daily reports, and ensuring

quality control

Zakhem Engineers, Beirut, Lebanon, summer 1999

Internship

Laboratory work (taking and testing specimens) of a highway project

TEACHING EXPERIENCE

Florida State University, Tallahassee, FL, summer 2006

Adjunct Instructor for EGM 3512-Engineering Mechanics

Florida State University, Tallahassee, FL, 2004 - to date

Teaching Assistant to Dr. AbdelRazig

Assisted in preparation of the course notes, homework, labs, tutoring students during

office hours

Courses assisted: CCE 4004-Construction Engineering, CEG 2202-Site Investigation,

TTE 3004-Transportation Engineering, EGM 3512-Engineering Mechanics

200

WORK EXPERIENCE

Zamil Steel Khobar, Saudi Arabia, 2003-2004

Project & Sales Engineer

Design, Estimate, and Schedule of Pre-Engineered Steel building. Assist in creation of

project proposals by securing project specifications from clients and communicating the

same to design teams. Liaison with client during proposal/quotation stage until projects

are awarded. Provide support to client and design team during project implementation.

PROFESSIONAL DEVELOPMENT ACTIVITIES

University-wide teaching Conference (spring 2006)

Workshop & Seminars

o Using Group Activities

o Advances PowerPoint

o Mentor Training Workshop

o Using Feedback to Improve Teaching Skills

o Leading Class Discussions

o Designing New Courses

o Aligning Your Teaching Philosophy with Learning Objectives

o Developing a Learner-Centered Syllabus

o Applying Creative Thinking Techniques in the Classroom

o Cultural, Instructional, and Language Issues in the Classroom

Preparing Future Faculty (PFF)

Electronic Campus

o New Features in Blackboard

o Blackboard Uploading Content

o Advanced PowerPoint

201

o Blackboard Communication

o Blackboard Grading and Assessments

FAMU Researchers Workshop Series

o Elements of Proposal Development

o A Primer for a Successful Grant

o Do’s and Don’ts of Collaboration

PUBLICATIONS

Ghanem, A., AbdelRazig, Y.: “Real time Construction Project Progress Tracking: A

Utility Function Model for Technology Evaluation and Selection”, to be presented in the

Construction Research Congress, Grand Bahamas Island, May 2007

Ghanem, A., AbdelRazig, Y., and Mehdi, S. M.: “Evaluation of a Real Time

Construction Project Progress Tracking”, to be presented in Joint International

Conference on Construction Culture, Innovation, and Management, Dubai, UAE,

November, 2006

El-Gafy, M., Ghanem, A.: “Resource Allocation in repetitive Construction Schedules

using Ant Colony Optimization”, to be presented in Joint International Conference on

Construction Culture, Innovation, and Management, Dubai, UAE, November, 2006

Ghanem, A., Abichoux, T., and AbdelRazig, Y.: “Sprayfield Technology to Treat

Wastewater Treatment Plant Effluent”, accepted in the 3rd International Conference on

Water Resources in Mediterranean Basin, Tripoli, Lebanon, November, 2006

Ghanem, A., and AbdelRazig, Y.: “Evaluation of Wireless Technologies in

Construction”, proceeding of the International Conference on Construction and Real

Estate Management, 13th Rinker International Conference, Orlando, Florida, October,

2006

Ghanem, A., and AbdelRazig, Y.: “A Framework for Real Time Construction Project

Progress Tracking”, proceeding of the 10th International Conference on Engineering,

Construction and Operations in Challenging Environments, Houston, Texas, March, 2006

El-Gafy, M., AbdelRazig, Y., and Ghanem, A.: “Dynamic Construction Site Layout

Using Ant Colony Optimization”, proceeding of the 85th meeting of the Transportation

Research Board (TRB), Washington DC., February, 2006

202

Ghanem, A., Mehdi S., and AbdelRazig, Y.: “Risk Management in Engineering Design

Projects”, the Journal of Project Management, under review

Ghanem, A., Oberlender, G.: “Six Sigma in Construction Projects”, creative components

submitted as fulfillment of Master Degree

Ghanem, A., Chatila, W.: “Management and Rehabilitation of an Existing Building”, thesis

submitted as fulfillment of Bachelor Degree

LISTINGS

Who's who in the USA Chancellor's list, 2004-2005

AFFILIATIONS

PHI KAPPA PHI (Oklahoma Chapter) Honor Society for excelling school

achievements: Member since 2002

Tau Beta Pi (Florida Etta Chapter) Engineering Honor Society: Member since 2005

(Treasurer)

Fiatech Student Member, Involved with Smart Chips project since 2006

Congress of Graduate Students Representing College of Engineering (Chair of

housing, parking & Transportation Committee)

American Society of Civil Engineers (ASCE): Student member since 2001

Oklahoma State University Alumni Association: Member since 2003

Lebanese Engineers Syndicate: Member since 2001

Arab Cultural Association (ACA)

Editorship & Professional Services

Associated School of Construction: Reviewer for the 43rd

ASC International

Conference

Habitat for Humanity: Volunteer

203

AWARDS

The Conference Presentation Grant. Awarded by the Florida State University Office of

Graduate Studies to assist in Conference presentation, (March 2006 and October 2006).

The Dissertation Research Grant. Awarded by the Florida State University Office of

Graduate Studies to assist the research of my dissertation, October 2006.

Best Teaching Award. Nominated by the Florida State University for best Teaching

Assistant, March 2007